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Relevant bibliographies by topics / Semantic video coding

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Journal articles
Dissertations / Theses
Book chapters
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Academic literature on the topic 'Semantic video coding'

Author: Grafiati

Published: 1 June 2024

Last updated: 31 July 2025

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Journal articles on the topic "Semantic video coding"

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Qiyuan, Du, Duan Yiping, and Tao Xiaoming. "Facial video semantic coding for semantic communication." China Communications 22, no. 6 (2025): 83–100. https://doi.org/10.23919/jcc.ja.2023-0606.

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Essel, Daniel Danso, Ben-Bright Benuwa, and Benjamin Ghansah. "Video Semantic Analysis." International Journal of Computer Vision and Image Processing 11, no. 2 (2021): 1–21. http://dx.doi.org/10.4018/ijcvip.2021040101.

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Sparse Representation (SR) and Dictionary Learning (DL) based Classifier have shown promising results in classification tasks, with impressive recognition rate on image data. In Video Semantic Analysis (VSA) however, the local structure of video data contains significant discriminative information required for classification. To the best of our knowledge, this has not been fully explored by recent DL-based approaches. Further, similar coding findings are not being realized from video features with the same video category. Based on the foregoing, a novel learning algorithm, Sparsity based Local

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Chen, Sovann, Supavadee Aramvith, and Yoshikazu Miyanaga. "Learning-Based Rate Control for High Efficiency Video Coding." Sensors 23, no. 7 (2023): 3607. http://dx.doi.org/10.3390/s23073607.

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High efficiency video coding (HEVC) has dramatically enhanced coding efficiency compared to the previous video coding standard, H.264/AVC. However, the existing rate control updates its parameters according to a fixed initialization, which can cause errors in the prediction of bit allocation to each coding tree unit (CTU) in frames. This paper proposes a learning-based mapping method between rate control parameters and video contents to achieve an accurate target bit rate and good video quality. The proposed framework contains two main structural codings, including spatial and temporal coding.

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Benuwa, Ben-Bright, Yongzhao Zhan, Benjamin Ghansah, Ernest K. Ansah, and Andriana Sarkodie. "Sparsity Based Locality-Sensitive Discriminative Dictionary Learning for Video Semantic Analysis." Mathematical Problems in Engineering 2018 (August 5, 2018): 1–11. http://dx.doi.org/10.1155/2018/9312563.

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Dictionary learning (DL) and sparse representation (SR) based classifiers have greatly impacted the classification performance and have had good recognition rate on image data. In video semantic analysis (VSA), the local structure of video data contains more vital discriminative information needed for classification. However, this has not been fully exploited by the current DL based approaches. Besides, similar coding findings are not being realized from video features with the same video category. Based on the issues stated afore, a novel learning algorithm, called sparsity based locality-sen

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Antoszczyszyn, P. M., J. M. Hannah, and P. M. Grant. "Reliable tracking of facial features in semantic-based video coding." IEE Proceedings - Vision, Image, and Signal Processing 145, no. 4 (1998): 257. http://dx.doi.org/10.1049/ip-vis:19982153.

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NOMURA, Yoshihiko, Ryutaro MATSUDA, Ryota Sakamoto, Tokuhiro SUGIURA, Hirokazu Matsui, and Norihiko KATO. "2301 Low Bit-Rate Semantic Coding Technology for Lecture Video." Proceedings of the JSME annual meeting 2005.7 (2005): 89–90. http://dx.doi.org/10.1299/jsmemecjo.2005.7.0_89.

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Pimentel-Niño, M. A., Paresh Saxena, and M. A. Vazquez-Castro. "Reliable Adaptive Video Streaming Driven by Perceptual Semantics for Situational Awareness." Scientific World Journal 2015 (2015): 1–16. http://dx.doi.org/10.1155/2015/394956.

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A novel cross-layer optimized video adaptation driven by perceptual semantics is presented. The design target is streamed live video to enhance situational awareness in challenging communications conditions. Conventional solutions for recreational applications are inadequate and novel quality of experience (QoE) framework is proposed which allows fully controlled adaptation and enables perceptual semantic feedback. The framework relies on temporal/spatial abstraction for video applications serving beyond recreational purposes. An underlying cross-layer optimization technique takes into account

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Guo, Jia, Xiangyang Gong, Wendong Wang, Xirong Que, and Jingyu Liu. "SASRT: Semantic-Aware Super-Resolution Transmission for Adaptive Video Streaming over Wireless Multimedia Sensor Networks." Sensors 19, no. 14 (2019): 3121. http://dx.doi.org/10.3390/s19143121.

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There are few network resources in wireless multimedia sensor networks (WMSNs). Compressing media data can reduce the reliance of user’s Quality of Experience (QoE) on network resources. Existing video coding software, such as H.264 and H.265, focuses only on spatial and short-term information redundancy. However, video usually contains redundancy over a long period of time. Therefore, compressing video information redundancy with a long period of time without compromising the user experience and adaptive delivery is a challenge in WMSNs. In this paper, a semantic-aware super-resolution transm

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Stivaktakis, Radamanthys, Grigorios Tsagkatakis, and Panagiotis Tsakalides. "Semantic Predictive Coding with Arbitrated Generative Adversarial Networks." Machine Learning and Knowledge Extraction 2, no. 3 (2020): 307–26. http://dx.doi.org/10.3390/make2030017.

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In spatio-temporal predictive coding problems, like next-frame prediction in video, determining the content of plausible future frames is primarily based on the image dynamics of previous frames. We establish an alternative approach based on their underlying semantic information when considering data that do not necessarily incorporate a temporal aspect, but instead they comply with some form of associative ordering. In this work, we introduce the notion of semantic predictive coding by proposing a novel generative adversarial modeling framework which incorporates the arbiter classifier as a n

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Herranz, Luis. "Integrating semantic analysis and scalable video coding for efficient content-based adaptation." Multimedia Systems 13, no. 2 (2007): 103–18. http://dx.doi.org/10.1007/s00530-007-0090-0.

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Dissertations / Theses on the topic "Semantic video coding"

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Al-Qayedi, Ali. "Internet video-conferencing using model-based image coding with agent technology." Thesis, University of Essex, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.298836.

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Mitrica, Iulia. "Video compression of airplane cockpit screens content." Electronic Thesis or Diss., Institut polytechnique de Paris, 2021. http://www.theses.fr/2021IPPAT042.

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Cette thèse aborde le problème de l'encodage de la vidéo des cockpits d'avion. Le cockpit des avions de ligne modernes consiste en un ou plusieurs écrans affichant l'état des instruments de l'avion (par exemple, la position de l'avion telle que rapportée par le GPS, le niveau de carburant tel que lu par les capteurs dans les réservoirs, etc.,) souvent superposés au naturel images (par exemple, cartes de navigation, caméras extérieures, etc.). Les capteurs d'avion sont généralement inaccessibles pour des raisons de sécurité, de sorte que l'enregistrement du cockpit est souvent le seul moyen de

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Book chapters on the topic "Semantic video coding"

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Mezaris, Vasileios, Nikolaos Thomos, Nikolaos V. Boulgouris, and Ioannis Kompatsiaris. "Knowledge-Assisted Analysis of Video for Content-Adaptive Coding and Transmission." In Advances in Semantic Media Adaptation and Personalization. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-76361_11.

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Lin, Yu-Tzu, and Chia-Hu Chang. "User-aware Video Coding Based on Semantic Video Understanding and Enhancing." In Recent Advances on Video Coding. InTech, 2011. http://dx.doi.org/10.5772/16498.

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Thomas-Kerr, Joseph, Ian Burnett, and Christian Ritz. "What Are You Trying to Say? Format-Independent Semantic-Aware Streaming and Delivery." In Recent Advances on Video Coding. InTech, 2011. http://dx.doi.org/10.5772/16763.

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Cavallaro, Andrea, and Stefan Winkler. "Perceptual Semantics." In Multimedia Technologies. IGI Global, 2008. http://dx.doi.org/10.4018/978-1-59904-953-3.ch105.

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The design of image and video compression or transmission systems is driven by the need for reducing the bandwidth and storage requirements of the content while maintaining its visual quality. Therefore, the objective is to define codecs that maximize perceived quality as well as automated metrics that reliably measure perceived quality. One of the common shortcomings of traditional video coders and quality metrics is the fact that they treat the entire scene uniformly, assuming that people look at every pixel of the image or video. In reality, we focus only on particular areas of the scene. I

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Cavallaro, Andrea, and Stefan Winkler. "Perceptual Semantics." In Digital Multimedia Perception and Design. IGI Global, 2006. http://dx.doi.org/10.4018/978-1-59140-860-4.ch001.

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The design of image and video compression or transmission systems is driven by the need for reducing the bandwidth and storage requirements of the content while maintaining its visual quality. Therefore, the objective is to define codecs that maximize perceived quality as well as automated metrics that reliably measure perceived quality. One of the common shortcomings of traditional video coders and quality metrics is the fact that they treat the entire scene uniformly, assuming that people look at every pixel of the image or video. In reality, we focus only on particular areas of the scene. I

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Conference papers on the topic "Semantic video coding"

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Samarathunga, Prabhath, Udara Jayasinghe, Yasith Ganearachchi, Thanuj Fernando, Nimesha Senanayake, and Anil Fernando. "Semantic Communication Based Lossless Distributed Video Coding for Error Prone Channels." In 2025 IEEE International Conference on Consumer Electronics (ICCE). IEEE, 2025. https://doi.org/10.1109/icce63647.2025.10929820.

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Jing, Zhao, Zhisong Bie, Haobo Lei, Jiali Wang, Yichen Zhi, and Hongxia Bie. "Semantic-Aware Source Coding for Talking-Head Video with Adaptive Keypoints." In 2025 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2025. https://doi.org/10.1109/wcnc61545.2025.10978751.

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Décombas, M., F. Capman, E. Renan, F. Dufaux, and B. Pesquet-Popescu. "Seam carving for semantic video coding." In SPIE Optical Engineering + Applications, edited by Andrew G. Tescher. SPIE, 2011. http://dx.doi.org/10.1117/12.895317.

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Silva, Michel M., Mario F. M. Campos, and Erickson R. Nascimento. "Semantic Hyperlapse: a Sparse Coding-based and Multi-Importance Approach for First-Person Videos." In XXXII Conference on Graphics, Patterns and Images. Sociedade Brasileira de Computação - SBC, 2019. http://dx.doi.org/10.5753/sibgrapi.est.2019.8302.

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The availability of low-cost, high-quality personal wearable cameras combined with the unlimited storage capacity of video-sharing websites has evoked a growing interest in First-Person Videos (FPVs). Such videos are usually composed of long-running unedited streams captured by a device attached to the user body, which makes them tedious and visually unpleasant to watch. Consequently, there is a rise in the need to provide quick access to the information therein. To address this need, efforts have been applied to the development of techniques such as Hyperlapse and Semantic Hyperlapse, which a

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Zhu, Chen, Guo Lu, Rong Xie, and Li Song. "Perceptual Video Coding Based on Semantic-Guided Texture Detection and Synthesis." In 2022 Picture Coding Symposium (PCS). IEEE, 2022. http://dx.doi.org/10.1109/pcs56426.2022.10018028.

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Silva, Michel M., Mario F. M. Campos, and Erickson R. Nascimento. "Semantic Hyperlapse: a Sparse Coding-based and Multi-Importance Approach for First-Person Videos." In Concurso de Teses e Dissertações da SBC. Sociedade Brasileira de Computação - SBC, 2020. http://dx.doi.org/10.5753/ctd.2020.11364.

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The availability of low-cost and high-quality wearable cameras combined with the unlimited storage capacity of video-sharing websites have evoked a growing interest in First-Person Videos. Such videos are usually composed of long-running unedited streams captured by a device attached to the user body, which makes them tedious and visually unpleasant to watch. Consequently, it raises the need to provide quick access to the information therein. We propose a Sparse Coding based methodology to fast-forward First-Person Videos adaptively. Experimental evaluations show that the shorter version video

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Yang, Jianping, Jie Zhang, and Xiangjun Chen. "Semantic-preload video model based on VOP coding." In 2012 International Conference on Graphic and Image Processing, edited by Zeng Zhu. SPIE, 2013. http://dx.doi.org/10.1117/12.2012827.

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Galteri, Leonardo, Marco Bertini, Lorenzo Seidenari, Tiberio Uricchio, and Alberto Del Bimbo. "Increasing Video Perceptual Quality with GANs and Semantic Coding." In MM '20: The 28th ACM International Conference on Multimedia. ACM, 2020. http://dx.doi.org/10.1145/3394171.3413508.

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Xie, Guangqi, Xin Li, Shiqi Lin, et al. "Hierarchical Reinforcement Learning Based Video Semantic Coding for Segmentation." In 2022 IEEE International Conference on Visual Communications and Image Processing (VCIP). IEEE, 2022. http://dx.doi.org/10.1109/vcip56404.2022.10008806.

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Hu, Yujie, Youmin Xu, Jianhui Chang, and Jian Zhang. "Semantic Neural Rendering-based Video Coding: Towards Ultra-Low Bitrate Video Conferencing." In 2022 Data Compression Conference (DCC). IEEE, 2022. http://dx.doi.org/10.1109/dcc52660.2022.00067.

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