Relevant bibliographies by topics / Videos

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Videos'

Author: Grafiati
Published: 4 June 2021
Last updated: 8 March 2025

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Journal articles on the topic "Videos"

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Aharonson, Vered, and Jared Joselowitz. "On Presenters and Commenters in YouTube Climate Change Videos." European Conference on Social Media 11, no. 1 (May 21, 2024): 9–12. http://dx.doi.org/10.34190/ecsm.11.1.2076.

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Social media videos can promote viewers responsibility to solve social problems such as climate change. Not all aspiring videos, however, are successful in persuading their viewers on the perils involved in climate change and on the need for pro-environmental behaviour. Our study examined attributes that could explain a video’s persuasiveness and focused on the video presenter traits. Videos on climate change were sourced from YouTube conjointly with the comments they elicited. The presenters in these videos addressed the negative effects and dangers of climate change and the role of human activity in resolving them. Two attributes were manually coded for each video: the type of presenter in the videos– scientist, politician or celebrity, and their presentation style: blaming, stating the problem, or suggesting a solution. A measure of persuasiveness was computed from the YouTubers comments using sentiment analysis. This computation provided a polarity label – positive, negative, or neutral, for all comments, for each video. Subsets of 50 comments per video were manually coded to validate the computational analysis. The findings indicated that a predominant number of positive-polarity comments was elicited by video presenters who were scientists. Videos that proposed potential solutions to climate change elicited a majority of positive polarity. Politicians and celebrity presenters, as well as blame-oriented videos elicited a larger number of negative-polarity comments. These initial findings imply a potential of sentiment analysis of comments to elucidate which attributes can increase a video’s persuasiveness on its viewers. This insight can improve future video production and enhance their influence.
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Aldukhayel, Dukhayel. "The Benefits of Social Media Comments to L2 Listening Comprehension." SAGE Open 13, no. 2 (April 2023): 215824402311713. http://dx.doi.org/10.1177/21582440231171320.

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The purpose of this study is to determine whether a rich repertoire of meaningful, relevant comments posted on social media sites can facilitate or increase L2 listeners’ comprehension of videos. The study utilized a quasi-experimental design with an experimental group ( n = 29) that watched two YouTube videos and read comments, as well as a control group ( n = 31) that watched the same videos without comments. After watching each video, students in both groups wrote summaries of the video content, and only the experimental students responded to brief questionnaires assessing their perceptions of the video’s comments. T-tests revealed that summaries written by the experimental group had significantly more, and also more informed and accurate, unit ideas. Results of the questionnaires revealed that there is a generally positive attitude toward comments as an L2 listening help option. These findings suggest that social media comments may be a useful tool to assist or enrich listening comprehension of videos. Pedagogically, when social media videos are selected for teaching or learning L2 listening, the richness, relevance, and meaningfulness of comments should be among the video’s selection criteria.
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Park, Minsu, Mor Naaman, and Jonah Berger. "A Data-Driven Study of View Duration on YouTube." Proceedings of the International AAAI Conference on Web and Social Media 10, no. 1 (August 4, 2021): 651–54. http://dx.doi.org/10.1609/icwsm.v10i1.14781.

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Video watching had emerged as one of the most frequent media activities on the Internet. Yet, little is known about how users watch online video. Using two distinct YouTube datasets, a set of random YouTube videos crawled from the Web and a set of videos watched by participants tracked by a Chrome extension, we examine whether and how indicators of collective preferences and reactions are associated with view duration of videos. We show that video view duration is positively associated with the video's view count, the number of likes per view, and the negative sentiment in the comments. These metrics and reactions have a significant predictive power over the duration the video is watched by individuals. Our findings provide a more precise understandings of user engagement with video content in social media beyond view count.
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Naik, Sachin, Abdulaziz Abdullah Al-Kheraif, and Sajith Vellappally. "Artificial intelligence in dentistry: Assessing the informational quality of YouTube videos." PLOS ONE 20, no. 1 (January 2, 2025): e0316635. https://doi.org/10.1371/journal.pone.0316635.

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Background and purpose The most widely used social media platform for video content is YouTubeTM. The present study evaluated the quality of information on YouTubeTM on artificial intelligence (AI) in dentistry. Methods This cross-sectional study used YouTubeTM (https://www.youtube.com) for searching videos. The terms used for the search were "artificial intelligence in dentistry," "machine learning in dental care," and "deep learning in dentistry." The accuracy and reliability of the information source were assessed using the DISCERN score. The quality of the videos was evaluated using the modified Global Quality Score (mGQS) and the Journal of the American Medical Association (JAMA) score. Results The analysis of 91 YouTube™ videos on AI in dentistry revealed insights into video characteristics, content, and quality. On average, videos were 22.45 minutes and received 1715.58 views and 23.79 likes. The topics were mainly centered on general dentistry (66%), with radiology (18%), orthodontics (9%), prosthodontics (4%), and implants (3%). DISCERN and mGQS scores were higher for videos uploaded by healthcare professionals and educational content videos(P<0.05). DISCERN exhibited a strong correlation (0.75) with the video source and with JAMA (0.77). The correlation of the video’s content and mGQS, was 0.66 indicated moderate correlation. Conclusion YouTube™ has informative and moderately reliable videos on AI in dentistry. Dental students, dentists and patients can use these videos to learn and educate about artificial intelligence in dentistry. Professionals should upload more videos to enhance the reliability of the content.
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Nugraha, Nalika Ligar Katiasa, Sudarya Permana, and Imas Wahyu Agustina. "Unveiling Creativity Elements in YouTube Narrative Videos for Ninth-Grade Junior High School Students." Stairs 4, no. 2 (February 21, 2024): 135–46. http://dx.doi.org/10.21009/stairs.4.2.5.

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Creative narrative videos posted on YouTube have been proven to help students learn the narrative text and enhance students’ creativity toward making an excellent creative product. Along with the advantages, there are challenges and risks that teachers must consider since YouTube is an open-access video-sharing platform. This study aims to see whether narrative videos posted on YouTube meet creativity elements that can help ninth-grade junior high school students learn narrative text. This study used a qualitative method with content analysis to analyze fifteen narrative videos from three YouTube channels; Dongeng Kita, English Fairy Tales, and Gigglebox. The selected fifteen videos have been uploaded within the last seven years and are addressed to teenage viewers. Using the framework from D'Souza (2021), the findings show that the selected narrative videos fulfilled around 30% to 80% of the creativity elements. The audience immersive experience aspect, with a percentage of 45%, is the most dominant aspect of the narrative video's creativity elements. In contrast, the development and control aspect is the least in the creativity elements of narrative video, with a percentage of 25,5%. The narrative videos demonstrate diversity, a distinction or feature that distinguishes a narrative video from the previous version (narrative text). This study is expected to be a recommendation for teachers in choosing narrative videos on YouTube to support their teaching materials and simultaneously enhance students' creative thinking skills.
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Joshi, Prof Indira. "Video Summarization for Marathi Language." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (May 3, 2024): 1–5. http://dx.doi.org/10.55041/ijsrem32024.

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The Video Summarization Platform using Python Flask is a comprehensive tool designed to summarize Marathi and English videos while providing summaries in Hindi, Marathi, and English languages. Leveraging machine learning and natural language processing (NLP) techniques, this platform offers a sophisticated solution for efficiently extracting key information from videos. The platform begins by transcribing the audio content of the video into text using automatic speech recognition (ASR) technology. This transcription process ensures that the platform can accurately analyze and summarize the video's content. Next, the text is translated into the target languages, namely Hindi, Marathi, and English, enabling users from diverse linguistic backgrounds to access the summarized content. To generate concise and informative summaries, advanced NLP algorithm is applied. This algorithm analyze the transcribed text to identify the most significant phrases, sentences, and concepts. By considering factors such as keyword frequency, semantic relevance, and context, the platform effectively distils the video's content into digestible summaries. Additionally, machine learning models are employed to classify the type of video content. These models are trained on diverse datasets encompassing various video genres and topics. By recognizing patterns and features within the video content, the platform can accurately categorize videos into distinct types, such as news, interviews, tutorials, or entertainment. The platform's user interface, powered by Python Flask, offers a seamless experience for users to upload videos, select their preferred language for summarization, and receive concise summaries in their chosen languages. The intuitive design ensures accessibility and ease of use, catering to both novice and advanced users. Overall, the Video Summarization Platform serves as a valuable resource for individuals seeking efficient ways to consume multimedia content. Whether for educational, informational, or entertainment purposes, this platform empowers users to access summarized video content in multiple languages, facilitated by cutting-edge machine learning and NLP technologies. Key Words: Transcription, Marathi-speaking users, Marathi YouTube videos, video content, transcription, summary, translation, Natural Language Toolkit (NLTK), content comprehension, user interaction data, past summaries, recommendation
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Zhang, Bin, Jia Lun Song, Zheng Zheng Liu, and Hai Ji. "The Micro-Video Label Classification System Design Based on Network Data Acquisition." Applied Mechanics and Materials 738-739 (March 2015): 556–59. http://dx.doi.org/10.4028/www.scientific.net/amm.738-739.556.

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Micro-video label classification system (MLCS) is designed to tag and classify micro-videos by a specific set of labels, which are extracted from users’ comments on the internet. These labels not only describe the micro-video’s features in various aspects, but also deliver the audiences’ attitudes and concern. Combining the high-ranking labels can effectively organize the creative elements to help producing new video scripts and categories. It breaks the traditional limit of linear producing process and makes the micro-videos’ story more topical and integrate.
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Ulusoy, Habibe Öztürk, and Raif Alan. "Is YouTubeTM the right address to get information on providing hygienic care for dental prostheses users?" Medical Science and Discovery 10, no. 4 (April 19, 2023): 250–56. http://dx.doi.org/10.36472/msd.v10i4.929.

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Objective: Patients increasingly use social media platforms such as YouTubeTM to get information about health issues. However, the effect of the videos on YouTubeTM on oral health care is still controversial. This study aimed to analyze the content quality of the videos on YouTubeTM about the oral hygiene care of various dental prostheses. Material and Methods: YouTubeTM videos were searched utilizing operators and keywords: «* (denture OR prosthesis OR implant) hygiene OR care OR cleaning OR brushing OR maintenance». The videos were ordered by "relevance". The video's source, origin, and content; duration; the number of likes, dislikes, comments, and views; the number of days since upload; viewing rate and viewer interactions were recorded for each video. In addition, videos were scored for the usefulness of their content: poor (0), moderate (1), or excellent (2). Results: 200 videos were screened, and 82 videos that met the criteria were analyzed in the study. It was found that most of the videos (72.2%) were uploaded from the USA, and the popular video topics were about complete dentures and implant-supported fixed dentures (48.8% and 43.9%, respectively). It has been observed that the usefulness score of the videos, which ranges from 0 to 2 and has an average of 1.06, had a positive and significant correlation with the number of likes and viewer interactions separately. Conclusion: Social media usage can be an effective tool for patients to learn about oral hygienic care for dental prostheses. However, it should be noted that YouTubeTM may also contain misleading information due to its dynamic nature. Healthcare professionals can be important in directing patients to videos with correct and qualified content.
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Haymes, A. T., and V. Harries. "‘How to stop a nosebleed’: an assessment of the quality of epistaxis treatment advice on YouTube." Journal of Laryngology & Otology 130, no. 8 (June 27, 2016): 749–54. http://dx.doi.org/10.1017/s0022215116008410.

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AbstractObjective:Video hosting websites are increasingly being used to disseminate health education messages. This study aimed to assess the quality of advice contained within YouTube videos on the conservative management of epistaxis.Method:YouTube.com was searched using the phrase ‘how to stop a nosebleed’. The first 50 videos were screened. Objective advice scores and subjective production quality scores were attributed by independent raters.Results:Forty-five videos were analysed. The mean advice score was 2.0 out of 8 and the mean production quality score was 1.6 out of 3. There were no correlations between a video's advice score and its search results rank (ρ = −0.28, p = 0.068), its view count (ρ = 0.20, p = 0.19) or its number of ‘likes’ (ρ = 0.21, p = 0.18).Conclusion:The quality of information on conservative epistaxis management within YouTube videos is extremely variable. A high search rank is no indication of video quality. Many videos proffer inappropriate and dangerous ‘alternative’ advice. We do not recommend YouTube as a source for patient information.
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Bopp, Trevor, Joshua D. Vadeboncoeur, Michael Stellefson, and Melissa Weinsz. "Moving Beyond the Gym: A Content Analysis of YouTube as an Information Resource for Physical Literacy." International Journal of Environmental Research and Public Health 16, no. 18 (September 10, 2019): 3335. http://dx.doi.org/10.3390/ijerph16183335.

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The Internet, and particularly YouTube, has been found to be and continues to develop as a resourceful educational space for health-related information. Understanding physical literacy as a lifelong health-related outcome and facilitator of an active lifestyle, we sought to assess the content, exposure, engagement, and information quality of uploaded physical literacy videos on YouTube. Two researchers collected 300 YouTube videos on physical literacy and independently coded each video’s: title, media source of upload, content topics related to physical literacy, content delivery style, and adherence to adapted Health on the Net Foundation Code of Conduct (HONcode) principles of information quality. Physical literacy videos that focused on physical activity and behaviors were the strongest predictor of high quality ratings, followed closely by videos covering affective domains (motivation, confidence, and self-esteem) of physical literacy. The content delivery method was also important, with videos utilizing presentations and testimonials containing high quality information about physical activity. Thus, providers of physical literacy and health-related online video content should be aware of and adhere to the expected quality standards. As health information expectations and ethical standards increase, the Internet, and specifically YouTube, has the potential to enhance video resources, virtual networking opportunities, as well as the sharing, dissemination, accumulation, and enrichment of physical literacy information for all.
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Dissertations / Theses on the topic "Videos"

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Lindskog, Eric, and Wrang Jesper. "Design of video players for branched videos." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-148592.

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Interactive branched video allows users to make viewing decisions while watching, that affect the playback path of the video and potentially the outcome of the story. This type of video introduces new challenges in terms of design, for example displaying the playback progress, the structure of the branched video as well as the choices that the viewers can make. In this thesis we test three implementations of working video players with different types of playback bars: one fully viewed with no moving parts, one that zooms into the currently watched section of the video, and one that leverages a fisheye distortion. A number of usability tests are carried out using surveys complemented with observations made during the tests. Based on these user tests we concluded that the implementation with a zoomed in playback bar was the easiest to understand and that fisheye effect received mixed results, ranging from distracting and annoying to interesting and clear. With this feedback a new set of implementations was created and solutions for each component of the video player were identified. These new implementations support more general solutions for the shape of the branch segments and the position and location of the choices for upcoming branches. The new implementations have not gone through any testing, but we expect that future work can further explore this subject with the help of our code and suggestions.
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Ogata, Atsushi. "Meditative videos." Thesis, Massachusetts Institute of Technology, 1988. http://hdl.handle.net/1721.1/78990.

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Thesis (M.S.V.S.)--Massachusetts Institute of Technology, Dept. of Architecture, 1988.
Includes bibliographical references (leaves 82-85). Filmography: leaves 86-87. Videography: leaves 88-92.
My intention is to provide "meditative" moments to all of us who must struggle with the fast pace of the modern world. These "meditative" moments are both calming and engaging. They resemble the moment of "satori," or "opening of mind," in Zen. Zen, embedded in the culture of Japan, is closely related to my work and sensibility. In realizing my intention, I have chosen the medium of video. Video can reach a wide audience through broadcasting and home videos. Its photographic ability allows us to directly record and celebrate our natural environment. As video is an experience in time, it can create quiet soothing sounds and slow subtle movements. It allows us time to "tune in" to the rhythm of the piece. In my video work, I depict basic natural elements such as light, water, and clouds, and their relationship to animate beings.
by Atsushi Ogata.
M.S.V.S.
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Stewart, Richard Christopher. "Effective audio for music videos : the production of an instructional video outlining audio production techniques for amateur music videos." Instructions for remote access. Click here to access this electronic resource. Access available to Kutztown University faculty, staff, and students only, 1996. http://www.kutztown.edu/library/services/remote_access.asp.

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Sedlařík, Vladimír. "Informační strategie firmy." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2012. http://www.nusl.cz/ntk/nusl-223526.

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This thesis analyzes the YouTube service and describes its main deficiencies. Based on theoretical methods and analyses, its main goal is to design a service that will solve the main YouTube problems, build a company around this service and introduce this service to the market. This service will not replace YouTube, but it will supplement it. Further, this work will suggest a possible structure, strategy and information strategy of this new company and its estimated financial results in the first few years.
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Lindgren, Björn. "Erfarenheter och åsikter om videos : Instrumentlärare om videos som undervisningsmaterial." Thesis, Linnéuniversitetet, Institutionen för musik och bild (MB), 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-65800.

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I en undersökning vars syfte är att lyfta instrumentlärares erfarenheter och åsikter om videos som undervisningsmaterial har fem informanter intervjuats. Materialet som samlats in presenterar efter analys informanternas erfarenheter och åsikter genom Koehler och Mishras (2009) TPaCK-modell. Det som framgår efter analys är informanternas olika vilja, intresse och kunnande för att involvera videos och deras erfarenheter och åsikter om att involvera videos i sin undervisning. I resultatet presenteras en gemensam åsikt om videos som en visuell resurs där åskådaren både kan se och höra. Videos främsta egenskap är också enligt informanterna att verka som en möjlig förlängning av lektionen. I diskussionen framgår dock att videos inte är någon självklar del av undervisningen utan hänger på instrumentlärares intresse, kunnande och vilja att involvera videos i sin undervisning.
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Chen, Juan. "Content-based Digital Video Processing. Digital Videos Segmentation, Retrieval and Interpretation." Thesis, University of Bradford, 2009. http://hdl.handle.net/10454/4256.

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Recent research approaches in semantics based video content analysis require shot boundary detection as the first step to divide video sequences into sections. Furthermore, with the advances in networking and computing capability, efficient retrieval of multimedia data has become an important issue. Content-based retrieval technologies have been widely implemented to protect intellectual property rights (IPR). In addition, automatic recognition of highlights from videos is a fundamental and challenging problem for content-based indexing and retrieval applications. In this thesis, a paradigm is proposed to segment, retrieve and interpret digital videos. Five algorithms are presented to solve the video segmentation task. Firstly, a simple shot cut detection algorithm is designed for real-time implementation. Secondly, a systematic method is proposed for shot detection using content-based rules and FSM (finite state machine). Thirdly, the shot detection is implemented using local and global indicators. Fourthly, a context awareness approach is proposed to detect shot boundaries. Fifthly, a fuzzy logic method is implemented for shot detection. Furthermore, a novel analysis approach is presented for the detection of video copies. It is robust to complicated distortions and capable of locating the copy of segments inside original videos. Then, iv objects and events are extracted from MPEG Sequences for Video Highlights Indexing and Retrieval. Finally, a human fighting detection algorithm is proposed for movie annotation.
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Potapov, Danila. "Supervised Learning Approaches for Automatic Structuring of Videos." Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAM023/document.

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L'Interprétation automatique de vidéos est un horizon qui demeure difficile a atteindre en utilisant les approches actuelles de vision par ordinateur. Une des principales difficultés est d'aller au-delà des descripteurs visuels actuels (de même que pour les autres modalités, audio, textuelle, etc) pour pouvoir mettre en oeuvre des algorithmes qui permettraient de reconnaitre automatiquement des sections de vidéos, potentiellement longues, dont le contenu appartient à une certaine catégorie définie de manière sémantique. Un exemple d'une telle section de vidéo serait une séquence ou une personne serait en train de pêcher; un autre exemple serait une dispute entre le héros et le méchant dans un film d'action hollywoodien. Dans ce manuscrit, nous présentons plusieurs contributions qui vont dans le sens de cet objectif ambitieux, en nous concentrant sur trois tâches d'analyse de vidéos: le résumé automatique, la classification, la localisation temporelle.Tout d'abord, nous introduisons une approche pour le résumé automatique de vidéos, qui fournit un résumé de courte durée et informatif de vidéos pouvant être très longues, résumé qui est de plus adapté à la catégorie de vidéos considérée. Nous introduisons également une nouvelle base de vidéos pour l'évaluation de méthodes de résumé automatique, appelé MED-Summaries, ou chaque plan est annoté avec un score d'importance, ainsi qu'un ensemble de programmes informatiques pour le calcul des métriques d'évaluation.Deuxièmement, nous introduisons une nouvelle base de films de cinéma annotés, appelée Inria Action Movies, constitué de films d'action hollywoodiens, dont les plans sont annotés suivant des catégories sémantiques non-exclusives, dont la définition est suffisamment large pour couvrir l'ensemble du film. Un exemple de catégorie est "course-poursuite"; un autre exemple est "scène sentimentale". Nous proposons une approche pour localiser les sections de vidéos appartenant à chaque catégorie et apprendre les dépendances temporelles entre les occurrences de chaque catégorie.Troisièmement, nous décrivons les différentes versions du système développé pour la compétition de détection d'événement vidéo TRECVID Multimédia Event Detection, entre 2011 et 2014, en soulignant les composantes du système dont l'auteur du manuscrit était responsable
Automatic interpretation and understanding of videos still remains at the frontier of computer vision. The core challenge is to lift the expressive power of the current visual features (as well as features from other modalities, such as audio or text) to be able to automatically recognize typical video sections, with low temporal saliency yet high semantic expression. Examples of such long events include video sections where someone is fishing (TRECVID Multimedia Event Detection), or where the hero argues with a villain in a Hollywood action movie (Inria Action Movies). In this manuscript, we present several contributions towards this goal, focusing on three video analysis tasks: summarization, classification, localisation.First, we propose an automatic video summarization method, yielding a short and highly informative video summary of potentially long videos, tailored for specified categories of videos. We also introduce a new dataset for evaluation of video summarization methods, called MED-Summaries, which contains complete importance-scorings annotations of the videos, along with a complete set of evaluation tools.Second, we introduce a new dataset, called Inria Action Movies, consisting of long movies, and annotated with non-exclusive semantic categories (called beat-categories), whose definition is broad enough to cover most of the movie footage. Categories such as "pursuit" or "romance" in action movies are examples of beat-categories. We propose an approach for localizing beat-events based on classifying shots into beat-categories and learning the temporal constraints between shots.Third, we overview the Inria event classification system developed within the TRECVID Multimedia Event Detection competition and highlight the contributions made during the work on this thesis from 2011 to 2014
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Liu, Yunjun 1977. "Creating animated mosaic videos." Thesis, McGill University, 2005. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=84053.

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Animated mosaics are a traditional form of stop-motion animation created by arranging and rearranging small objects or tiles from frame to frame. While this animation style is uniquely compelling, the traditional process of manually placing and then moving tiles in each frame is time-consuming and laborious. Recent work has proposed algorithms for static mosaics, but generating temporally coherent mosaic animations has remained open. This thesis presents several contributions to the animated mosaic problem in the context of a larger system for creating mosaic animations. Specifically, this thesis describes contributions for enabling an animator to relatively quickly and easily specify the desired animation using Scalable Vector Graphics (SVG), as well as an initial exploration of 3D packing for mosaic animations based on a successful 2D packing approach.
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Cui, Yingnan S. M. Massachusetts Institute of Technology. "On learning from videos/." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/120233.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 95-97).
The robot phone disassembly task is difficult in many ways: It has requirements on high precision, high speed, and should be general to all types of cell phones. Previous works on robot learning from demonstration are hardly applicable due to the complexity of teaching, huge amounts of data and difficulty in generalization. To tackle these problems, we try to learn from videos and extract useful information for the robot. To reduce the amounts of data we need to process, we generate a mask for the video and observe only the region of interest. Inspired by the idea that spatio-temporal interest point (STIP) detector may give meaningful points such as the contact point between the tool and the part, we design a new method of detecting STIPs based on optical flow. We also design a new descriptor by modifying the histogram of optical flow. The STIP detector and descriptor together can make sure that the features are invariant to scale, rotation and noises. Using the modified histogram of optical flow descriptor, we show that even without considering raw pixels of the original video, we can achieve pretty good classification results.
by Yingnan Cui.
S.M.
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Touliatou, Georgia. "Diegetic stories in a video mediation : a narrative analysis of four videos." Thesis, University of Surrey, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.397132.

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Books on the topic "Videos"

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Goethe-Institut. Video Katalog: Videos for loan. London: Goethe-Institut, 1990.

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Rowley, Kay. Videos. New York: Crestwood House, 1992.

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B, Steve. Professional explainer videos: Explainer videos. Cleveland, USA.: Steve Press, 2015.

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Vachon, Ryan. Science Videos. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-69512-9.

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Risco N., Ana María (Risco Neira), 1968-, Cuneo Bruno, Iommi Alfonso 1976-, and Museo de Artes Visuales (Santiago, Chile), eds. Desierta: Pinturas aeropostales, videos = airmail paintings, videos. Santiago de Chile: Museo de Artes Visuales, 2010.

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Musée d'art moderne et contemporain de Strasbourg., ed. Videos topiques: Tours et retours de l'art video. Strasbourg: Musee d'art moderne et contemporain de Strasbourg, 2000.

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Videomaker, Inc. Creating action videos. Chico, CA: Videomaker, 2009.

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Willoughby, Nick. Making YouTube videos. Hoboken, New Jersey: John Wiley & Sons, Incorporated, 2015.

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Rae, Clare. Clare Rae: Videos. Melbourne: Beam Contemporary, 2012.

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John, Brogden. Barbara Hlali: Videos, Wandarbeiten, Zeichnungen = Videos, mural drawing, drawings. Bönen: Kettler, 2013.

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Book chapters on the topic "Videos"

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Oldenburg, Reinhard. "Videos." In Mathematische Algorithmen im Unterricht, 113–18. Wiesbaden: Vieweg+Teubner Verlag, 2011. http://dx.doi.org/10.1007/978-3-8348-8336-0_13.

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Dionne, Jean-Philippe. "Videos." In Presentation Skills for Scientists and Engineers, 37–44. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66069-7_5.

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Göbel, Lisa. "Videos." In Essener Beiträge zur Mathematikdidaktik, 155–202. Wiesbaden: Springer Fachmedien Wiesbaden, 2021. http://dx.doi.org/10.1007/978-3-658-32637-1_12.

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Wilson, Kevin. "Watching Videos." In Using Kindle Fire HD, 61–65. Berkeley, CA: Apress, 2014. http://dx.doi.org/10.1007/978-1-4842-0580-8_14.

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Trautschold, Martin, Rene Ritchie, and Gary Mazo. "Viewing Videos." In iPhone 4S Made Simple, 331–43. Berkeley, CA: Apress, 2012. http://dx.doi.org/10.1007/978-1-4302-3588-0_17.

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Burkat, Cat Nguyen. "Appendix: Videos." In Avoiding and Managing Complications in Cosmetic Oculofacial Surgery, 309. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51152-4_30.

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Bednarek, Monika, and Helen Caple. "Promotional Videos." In Values and Choices in Television Discourse, 5–30. London: Palgrave Macmillan UK, 2015. http://dx.doi.org/10.1057/9781137478474_1.

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Kirschall, Sonja. "Online-Videos." In Audiovision zwischen Hand und Haut, 452–56. Bielefeld, Germany: transcript Verlag, 2024. http://dx.doi.org/10.14361/9783839471289-021.

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Baskind, Eric. "Interactive videos." In Mooting, 298–300. 2nd ed. London: Routledge, 2024. http://dx.doi.org/10.4324/9781003385684-11.

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Irwin, Terry, Julie Terberg, and Echo Swinford. "Inserting videos." In Medical Presentations, 104–8. Boca Raton: CRC Press, 2024. http://dx.doi.org/10.1201/9781003287902-13.

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Conference papers on the topic "Videos"

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Liu, Yuanxin, Shicheng Li, Yi Liu, Yuxiang Wang, Shuhuai Ren, Lei Li, Sishuo Chen, Xu Sun, and Lu Hou. "TempCompass: Do Video LLMs Really Understand Videos?" In Findings of the Association for Computational Linguistics ACL 2024, 8731–72. Stroudsburg, PA, USA: Association for Computational Linguistics, 2024. http://dx.doi.org/10.18653/v1/2024.findings-acl.517.

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Islam, Md Mohaiminul, Ngan Ho, Xitong Yang, Tushar Nagarajan, Lorenzo Torresani, and Gedas Bertasius. "Video ReCap: Recursive Captioning of Hour-Long Videos." In 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 18198–208. IEEE, 2024. http://dx.doi.org/10.1109/cvpr52733.2024.01723.

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Matos, Diognei de, and Erickson R. Nascimento. "Musical Hyperlapse: A Multimodal Approach to Accelerate First-Person Videos." In Anais Estendidos da Conference on Graphics, Patterns and Images. Sociedade Brasileira de Computação - SBC, 2022. http://dx.doi.org/10.5753/sibgrapi.est.2022.23258.

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With the advance in technology and social media usage, first-person recording videos has become a common habit. These videos are usually very long and tiring to watch, bringing the need to speed up them. Despite recent progress of fast-forward methods, they do not consider inserting background music in the videos, which could make them more enjoyable. This thesis presents a new method that creates accelerated videos and includes the background music keeping the same emotion induced by visual and acoustic modalities. Our approach is based on the automatic recognition of emotions induced by music and video contents and an optimization algorithm that maximizes the visual quality of the output video and seeks to match the similarity of the music and the video’s emotions. Quantitative results show that our method achieves the best performance in matching emotion similarity while maintaining the visual quality of the output video compared with other literature methods. Visual results can be seen through the link: https://youtu.be/9ykQa9zhcz8.
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Li, Hao, Peng Jin, Zesen Cheng, Songyang Zhang, Kai Chen, Zhennan Wang, Chang Liu, and Jie Chen. "TG-VQA: Ternary Game of Video Question Answering." In Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}. California: International Joint Conferences on Artificial Intelligence Organization, 2023. http://dx.doi.org/10.24963/ijcai.2023/116.

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Video question answering aims at answering a question about the video content by reasoning the alignment semantics within them. However, since relying heavily on human instructions, i.e., annotations or priors, current contrastive learning-based VideoQA methods remains challenging to perform fine-grained visual-linguistic alignments. In this work, we innovatively resort to game theory, which can simulate complicated relationships among multiple players with specific interaction strategies, e.g., video, question, and answer as ternary players, to achieve fine-grained alignment for VideoQA task. Specifically, we carefully design a VideoQA-specific interaction strategy to tailor the characteristics of VideoQA, which can mathematically generate the fine-grained visual-linguistic alignment label without label-intensive efforts. Our TG-VQA outperforms existing state-of-the-art by a large margin (more than 5%) on long-term and short-term VideoQA datasets, verifying its effectiveness and generalization ability. Thanks to the guidance of game-theoretic interaction, our model impressively convergences well on limited data (10^4 videos), surpassing most of those pre-trained on large-scale data (10^7 videos).
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Zhao, Hongrui, Jin Yu, Yanan Li, Donghui Wang, Jie Liu, Hongxia Yang, and Fei Wu. "Dress like an Internet Celebrity: Fashion Retrieval in Videos." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/147.

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Nowadays, both online shopping and video sharing have grown exponentially. Although internet celebrities in videos are ideal exhibition for fashion corporations to sell their products, audiences do not always know where to buy fashion products in videos, which is a cross-domain problem called video-to-shop. In this paper, we propose a novel deep neural network, called Detect, Pick, and Retrieval Network (DPRNet), to break the gap between fashion products from videos and audiences. For the video side, we have modified the traditional object detector, which automatically picks out the best object proposals for every commodity in videos without duplication, to promote the performance of the video-to-shop task. For the fashion retrieval side, a simple but effective multi-task loss network obtains new state-of-the-art results on DeepFashion. Extensive experiments conducted on a new large-scale cross-domain video-to-shop dataset shows that DPRNet is efficient and outperforms the state-of-the-art methods on video-to-shop task.
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Akhter, Syed Humayun, and Rahman Md Mizanoor. "Framework for Implementing Educational Concept Videos at Bangladesh Open University." In Tenth Pan-Commonwealth Forum on Open Learning. Commonwealth of Learning, 2022. http://dx.doi.org/10.56059/pcf10.3749.

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Video has been widely used as an effective media for delivering varied educational contents through broadcast and/or web. Video-mediated learning has been expanded for its effectiveness, and no doubt, there is an evolution in the production of videos because of technological development. Now-a-day, one can make video rapidly without cost using his or her smartphone. In this way, characteristics of educational video have been changed and short duration videos are of very friendly to the mobile users, and the demand for concept video, also known as ‘explainer video’, is increasing day-by-day. In response, Bangladesh Open University (BOU) developed a framework for the effective use of educational concept videos. This paper discusses the framework for making concept video which consists of a methodology and design guidelines, and both are linked to learning objectives. Short duration concept videos prepared in the form of transformation of BOU texts using the framework was experimented in focus group discussions (FGDs) where it was compared with the long duration video lecture based on the same texts. This paper portrays the findings of FGDs. Results suggest for mainstreaming concept videos in the academic delivery at BOU.
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Schneider, Kurt, and Linda Marilena Bertolli. "Video Variants for CrowdRE: How to Create Linear Videos, Vision Videos, and Interactive Videos." In 2019 IEEE 27th International Requirements Engineering Conference Workshops (REW). IEEE, 2019. http://dx.doi.org/10.1109/rew.2019.00039.

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Allen, Cathryn, Bryson Payne, Tanirat Abegaz, and Chuck Robertson. "What You See Is Not What You Know: Deepfake Image Manipulation." In 2022 KSU CONFERENCE ON CYBERSECURITY EDUCATION, RESEARCH AND PRACTICE. Kennesaw State University, 2022. http://dx.doi.org/10.32727/28.2023.1.

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Research indicates that deceitful videos tend to spread rapidly online and influence people’s opinions and ideas. Because of this, video misinformation via deepfake video manipulation poses a significant online threat. This study aims to discover what factors can influence viewers’ capability of distinguishing deepfake videos from genuine video footage. This work focuses on exploring deepfake videos’ potential use for deception and misinformation by exploring people’s ability to determine whether videos are deepfakes in a survey consisting of deepfake videos and original unedited videos. The participants viewed a set of four videos and were asked to judge whether the videos shown were deepfakes or originals. The survey varied the familiarity that the viewers had with the subjects of the videos. Also, the number of videos shown at one time was manipulated. This survey showed that familiarity of subjects has a statistically significant impact on how well people can determine a deepfake. Notably, however, almost two thirds of study participants (102 out of 154, or 66.23%) were unable to correctly identify a sequence of just four videos as either genuine or deepfake. Overall, the study provides insights into possible methods for countering disinformation and deception resulting from the misuse of deepfakes.
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Singh, Gaurav. "Perceived Effectiveness of Videos as e-Content in MOOC." In Tenth Pan-Commonwealth Forum on Open Learning. Commonwealth of Learning, 2022. http://dx.doi.org/10.56059/pcf10.8414.

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Massive Open Online Courses (MOOCs) have gained momentum in the past decade. MOOCs are becoming popular day by day across the world. One visible difference between traditional teaching-learning and MOOC is in terms of the central position of videos. Video-based content delivery has become the primary medium of instruction in most the MOOCs (Yousef, 2015), supported by e-text, activities, quizzes, and discussion forums. In India, the MOOCs being offered on the SWAYAM platform are mostly video-based. As per SWAYAM guidelines (2016 & 2017), for a four-credit MOOC in SWAYAM, a minimum of 20 hours of video content is essential. The researcher has offered two MOOC courses of 16 weeks duration on SWAYAM platforms namely, Learning and Teaching (with enrolment of around 15000) and, Pedagogy of Science (with enrolment of around 5000) in two cycles, i.e., July 2020 and January 2021. Total 111 videos have been developed for these two courses and when the viewership data was analysed, it was found that except for the course introductory videos, the viewership of other videos was varied and some videos have nearly 2530 views only in six months, this triggered the researcher to undertake a study to find out the usability of videos in MOOC. The researcher has decided to find out the usability and perceived effectiveness of videos in MOOCs being offered on the SWAYAM platform. The outcomes of the study are based on the perception of learners in IGNOU-SWAYAM MOOC around various identified factors like duration and number; content quality and relevance, quality of graphics and animations; subject matter experts; language; and positioning of video in the module. The paper also suggests ways to improve the video component of MOOC to improve its effectiveness and usability.
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Arrambide-Leal, Eduardo J., Vianney Lara-Prieto, and Rebeca M. García-García. "Short Videos to Communicate Effectively to Engineering Students." In Seventh International Conference on Higher Education Advances. Valencia: Universitat Politècnica de València, 2021. http://dx.doi.org/10.4995/head21.2021.13002.

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The use of multimedia in education has become a basic tool for educators. As Millennials and Generation Z use technology in their everyday life, the educational model has been shifting towards the use of multimedia and technology to enhance the active learning process. The objective of this project was to design, produce and implement short educational or instructional videos to present content with a more active approach and measure the impact on their understanding and preference. A video with the content of graduation requirements was produced, shared with 240 seniors of Engineering Academic Programs. The results show that 97% of the students liked the video and the way the content was shared and 91.6% of the students find the video format useful. The results show that the learning process was active and effective. The exit poll also shows that 97% of the students think that there should be more educational videos on some other processes. This project included the design, production and implementation of 18 videos. This research describes the approach and impact of using short videos in engineering and transition from a traditional method of sharing content to students to a more active learning environment.Keywords:Educational Videos; Active and Collaborative Learning; Student Engagement; Educational Innovation; Higher Education.
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Reports on the topic "Videos"

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Patel, Deep, Kenneth Graf, and David Fuller. Hip Surgical Preparation Educational Video. Rowan Digital Works, January 2021. http://dx.doi.org/10.31986/issn.2689-0690_rdw.oer.1022.

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This series of open educational videos provides an in depth overview of various surgical preparation procedures. These instructional videos could be of interest to various medical and health science trainees in a variety of fields such as nursing or medicine. All patients featured in this video series have signed consent and release forms authorizing the release of these educational videos.
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Patel, Deep, Catherine Fedorka, and David Fuller. Shoulder Surgical Preparation Educational Video. Rowan Digital Works, January 2021. http://dx.doi.org/10.31986/issn.2689-0690_rdw.oer.1023.

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This series of open educational videos provides an in depth overview of various surgical preparation procedures. These instructional videos could be of interest to various medical and health science trainees in a variety of fields such as nursing or medicine. All patients featured in this video series have signed consent and release forms authorizing the release of these educational videos.
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Patel, Deep, Julio Rodriguez, Vishal Khatri, and David Fuller. Spine Surgical Preparation Educational Video. Rowan Digital Works, January 2021. http://dx.doi.org/10.31986/issn.2689-0690_rdw.oer.1021.

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This series of open educational videos provides an in depth overview of various surgical preparation procedures. These instructional videos could be of interest to various medical and health science trainees in a variety of fields such as nursing or medicine. All patients featured in this video series have signed consent and release forms authorizing the release of these educational videos.
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Patel, Deep, Eric Freeland, and David Fuller. Foot and Ankle Surgical Preparation Educational Video. Rowan Digital Works, January 2021. http://dx.doi.org/10.31986/issn.2689-0690_rdw.oer.1020.

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This series of open educational videos provides an in depth overview of various surgical preparation procedures. These instructional videos could be of interest to various medical and health science trainees in a variety of fields such as nursing or medicine. All patients featured in this video series have signed consent and release forms authorizing the release of these educational videos.
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Patel, Deep, Alisina Shahi, and David Fuller. Hand and Wrist Surgical Preparation Educational Video. Rowan Digital Works, January 2021. http://dx.doi.org/10.31986/issn.2689-0690_rdw.oer.1019.

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This series of open educational videos provides an in depth overview of various surgical preparation procedures. These instructional videos could be of interest to various medical and health science trainees in a variety of fields such as nursing or medicine. All patients featured in this video series have signed consent and release forms authorizing the release of these educational videos.
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Bingamon, Brian. Glove Box Training Videos. Office of Scientific and Technical Information (OSTI), July 2021. http://dx.doi.org/10.2172/1810520.

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Nyaga, Robert, Jaspreet Singh, and Steve Wendel. Can mass media videos encourage reading in children? Busara, January 2025. https://doi.org/10.62372/jyxj9942.

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Queen Rania Foundation (QRF) is rolling out an ambitious program to encourage parents in Jordan to improve early childhood literacy through shared reading practices with their children. . This program includes videos for social media messaging aimed at parents. Busara was engaged to review the video scripts through a behavioral lens, then work with QRF through January 2024 to tailor its rollout plan to facilitate iterative and rigorous learning about the impact of the program.
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Bai, Jiamin. Selectively De-animating and Stabilizing Videos. Fort Belvoir, VA: Defense Technical Information Center, December 2014. http://dx.doi.org/10.21236/ada620000.

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Castillo-Ruiz, Paz, and Charo Quesada. Violencia doméstica: Intervenciones para su prevención y tratamiento: 8: Producción y uso de un video: Vidas golpeadas, esperanzas destruidas. Inter-American Development Bank, December 2001. http://dx.doi.org/10.18235/0006126.

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El objetivo del presente folleto informativo es dar cuenta del proyecto piloto de producción y distribución del video documental "Vidas golpeadas, esperanzas destruidas: cuando el hombre maltrata a la mujer" (ATN/SF-5317-RG), del Banco Interamericano de Desarrollo (BID). Como parte del Paraguas Técnico-Violencia Doméstica se propuso llevar a cabo un proyecto para escribir una guía sobre la producción y el uso de videos documentales en la prevención y sensibilización contra la violencia doméstica, y hacer recomendaciones sobre la experiencia extraída de dicho proyecto.
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Anderson, Dylan, Crystal Painter, Annika O’Dea, Tyler Hesser, and Katherine Brodie. Rectifying and stabilizing Planet SkySat video collects for bathymetric inversions from space. Engineer Research and Development Center (U.S.), July 2024. http://dx.doi.org/10.21079/11681/48777.

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This Coastal and Hydraulics Engineering Technical Note (CHETN) presents the development of a workflow to process Planet SkySat videos collected from space at the US Army Engineer Research and Development Center (ERDC), Coastal and Hydraulics Laboratory (CHL), Field Research Facility (FRF), in Duck, North Carolina, to derive wave kinematics and perform bathymetric inversions. The document summarizes the nine 30–60 s* satellite video collections, demonstrates the accuracy of an automated rectification and stabilization workflow, and applies a new short-dwell version of a common inversion algorithm (cBathy) to demonstrate the utility of short-dwell videos from space providing an initial out-of-the-box assessment of errors for one of the collections, and recommends future avenues of research for improving bathymetric predictions.
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