Relevant bibliographies by topics / Foreground object

Contents

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

Academic literature on the topic 'Foreground object'

Author: Grafiati
Published: 4 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "Foreground object"

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Yinhui Zhang, Yinhui Zhang, and Zifen He Zifen He. "Foreground object extraction through motion segmentation." Chinese Optics Letters 13, s1 (2015): S11002–311006. http://dx.doi.org/10.3788/col201513.s11002.

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Wang, Jian, Yuesong Zhang, Fei Zhang, Yazhou Li, Lingcong Nie, and Jiale Zhao. "MegaDetectNet: A Fast Object Detection Framework for Ultra-High-Resolution Images." Electronics 12, no. 18 (2023): 3737. http://dx.doi.org/10.3390/electronics12183737.

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Addressing the challenge of efficiently detecting objects in ultra-high-resolution images during object detection tasks, this paper proposes a novel method called MegaDetectNet, which leverages foreground image for large-scale resolution image object detection. MegaDetectNet utilizes a foreground extraction network to generate a foreground image that highlights target regions, thus avoiding the computationally intensive process of dividing the image into multiple sub-images for detection, and significantly improving the efficiency of object detection. The foreground extraction network in MegaD
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Wang, Xinlong, Wei Yin, Tao Kong, Yuning Jiang, Lei Li, and Chunhua Shen. "Task-Aware Monocular Depth Estimation for 3D Object Detection." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 07 (2020): 12257–64. http://dx.doi.org/10.1609/aaai.v34i07.6908.

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Monocular depth estimation enables 3D perception from a single 2D image, thus attracting much research attention for years. Almost all methods treat foreground and background regions (“things and stuff”) in an image equally. However, not all pixels are equal. Depth of foreground objects plays a crucial role in 3D object recognition and localization. To date how to boost the depth prediction accuracy of foreground objects is rarely discussed. In this paper, we first analyze the data distributions and interaction of foreground and background, then propose the foreground-background separated mono
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Ye, Guosheng, Jianming Wang, and Zizhong Yang. "Efficient Object Placement via FTOPNet." Electronics 12, no. 19 (2023): 4106. http://dx.doi.org/10.3390/electronics12194106.

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Image composition involves the placement of foreground objects at an appropriate scale within a background image to create a visually realistic composite image. However, manual operations for this task are time-consuming and labor-intensive. In this study, we propose an efficient method for foreground object placement, comprising a background feature extraction module (BFEM) designed for background images and a foreground–background cross-attention feature fusion module (FBCAFFM). The BFEM is capable of extracting precise and comprehensive information from the background image. The fused featu
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Feng, Junying, Peng Liu, and Yong Kwan Kim. "Foreground Detection Based on Superpixel and Semantic Segmentation." Computational Intelligence and Neuroscience 2022 (August 31, 2022): 1–14. http://dx.doi.org/10.1155/2022/4331351.

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Foreground detection is an essential step in computer vision and video processing. Accurate foreground object extraction is crucial for subsequent high-level tasks such as target recognition and tracking. Although many foreground detection algorithms have been proposed, foreground detection in complex scenes is still a challenging problem. This paper presents a foreground detection algorithm based on superpixel and semantic segmentation. It first uses multiscale superpixel segmentation to obtain the initial foreground mask. At the same time, a semantic segmentation network is applied to separa
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Zhang, Xia Yi, Zhi Peng Li, Fu Qiang Liu, Zhen Jia, and Jian Wei Zhao. "An Optimization Algorithm of Foreground Objects Extraction." Advanced Materials Research 403-408 (November 2011): 169–76. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.169.

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In this paper, we propose a novel algorithm for coarse-to-fine foreground objects extraction. There are two general approaches for foreground objects extraction: background subtraction and image matting. Our new approach can not only improve detection accuracy compared with general background subtraction approaches, but also reduce computation burden compared with general image matting approaches. Firstly, we present a novel method called Motion-mask Gaussian Mixture Models (Motion-mask GMMs) to extract coarse foreground regions. This new approach can classify foreground and background pixels
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Han, Guangjie, Yintian Zhu, Lyuchao Liao, Huiwen Yao, Zhaolin Zhao, and Qi Zheng. "Hybrid Attention-Based 3D Object Detection with Differential Point Clouds." Electronics 11, no. 23 (2022): 4010. http://dx.doi.org/10.3390/electronics11234010.

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Object detection based on point clouds has been widely used for autonomous driving, although how to improve its detection accuracy remains a significant challenge. Foreground points are more critical for 3D object detection than background points; however, most current detection frameworks cannot effectively preserve foreground points. Therefore, this work proposes a hybrid attention-based 3D object detection method with differential point clouds, which we name HA-RCNN. The method differentiates the foreground points from the background ones to preserve the critical information of foreground p
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Beloborodov, D., and L. Mestetskiy. "FOREGROUND DETECTION ON DEPTH MAPS USING SKELETAL REPRESENTATION OF OBJECT SILHOUETTES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W4 (May 10, 2017): 7–11. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w4-7-2017.

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This article considers the problem of foreground detection on depth maps. The problem of finding objects of interest on images appears in many object detection, recognition and tracking applications as one of the first steps. However, this problem becomes too complicated for RGB images with multicolored or constantly changing background and in presence of occlusions. Depth maps provide valuable information about distance to the camera for each point of the scene, making it possible to explore object detection methods, based on depth features. We define foreground as a set of objects silhouette
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Rahul, Paul, and Mukhopadhyay Sushanta. "FOREGROUND OBJECT EXTACTION BASED ON INDEPENDENT COMPONENT ANALYSIS." Advances in Vision Computing: An International Journal (AVC) 2, no. 4 (2015): 01–11. https://doi.org/10.5281/zenodo.3445779.

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Moving objects are often characterized by coherent motion that is distinct from that of the background. This makes motion a very useful feature for segmenting video sequence. Extracting moving objects from videos is important for many applications like surveillance, traffic analysis etc. In this paper a novel and efficient moving object segmentation algorithm is proposed that is based on independent component analysis (ICA). Moving objects and static background are considered to be independent, so independent component analysis is applied on frames of a video sequence to identify the prelimina
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Rahul, Paul, and Mukhopadhyay Sushanta. "FOREGROUND OBJECT EXTACTION BASED ON INDEPENDENT COMPONENT ANALYSIS." Advances in Vision Computing: An International Journal (AVC) 2, no. 4 (2015): 01–11. https://doi.org/10.5281/zenodo.3611036.

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Moving objects are often characterized by coherent motion that is distinct from that of the background. This makes motion a very useful feature for segmenting video sequence. Extracting moving objects from videos is important for many applications like surveillance, traffic analysis etc. In this paper a novel and efficient moving object segmentation algorithm is proposed that is based on independent component analysis (ICA). Moving objects and static background are considered to be independent, so independent component analysis is applied on frames of a video sequence to identify the prelimina
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Dissertations / Theses on the topic "Foreground object"

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Huerta, Casado Ivan. "Foreground Object Segmentation and Shadow Detection for Video Sequences in Uncontrolled Environments." Doctoral thesis, Universitat Autònoma de Barcelona, 2010. http://hdl.handle.net/10803/5797.

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Aquesta tesis esta dividida en dos parts principalment. A la primera, es presenta un estudi dels problemes que es poden trobar en la segmentació per moviment, basant-se en aquest estudi es presenta un algoritme genèric el qual es capaç de solucionar d'una forma acurada la majoria dels problemes que es poden trobar en aquest tipus de segmentació. En la segona part, es tracta el tema de les ombres en profunditat. Primer, es presenta un algoritme bottom-up basat en un detector de ombres cromàtiques el qual es capaç no només de solucionar les ombres que es troben a la penombra, sinó també les ombr
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Yin, Li. "Adaptive Background Modeling with Temporal Feature Update for Dynamic Foreground Object Removal." DigitalCommons@USU, 2016. https://digitalcommons.usu.edu/etd/5040.

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In the study of computer vision, background modeling is a fundamental and critical task in many conventional applications. This thesis presents an introduction to background modeling and various computer vision techniques for estimating the background model to achieve the goal of removing dynamic objects in a video sequence. The process of estimating the background model with temporal changes in the absence of foreground moving objects is called adaptive background modeling. In this thesis, three adaptive background modeling approaches were presented for the purpose of developing \teacher remo
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Leoputra, Wilson Suryajaya. "Video foreground extraction for mobile camera platforms." Thesis, Curtin University, 2009. http://hdl.handle.net/20.500.11937/1384.

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Foreground object detection is a fundamental task in computer vision with many applications in areas such as object tracking, event identification, and behavior analysis. Most conventional foreground object detection methods work only in a stable illumination environments using fixed cameras. In real-world applications, however, it is often the case that the algorithm needs to operate under the following challenging conditions: drastic lighting changes, object shape complexity, moving cameras, low frame capture rates, and low resolution images. This thesis presents four novel approaches for fo
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Ergul, Mustafa. "A Fully Automatic Shape Based Geo-spatial Object Recognition." Master's thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614680/index.pdf.

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A great number of methods based on local features or global appearances have been proposed in the literature for geospatial object detection and recognition from satellite images. However, since these approaches do not have enough discriminative capabilities between object and non-object classes, they produce results with innumerable false positives during their detection process. Moreover, due to the sliding window mechanisms, these algorithms cannot yield exact location information for the detected objects. Therefore, a geospatial object recognition algorithm based on the object shape mask i
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Tzanidou, Giounona. "Carried baggage detection and recognition in video surveillance with foreground segmentation." Thesis, Loughborough University, 2014. https://dspace.lboro.ac.uk/2134/14989.

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Security cameras installed in public spaces or in private organizations continuously record video data with the aim of detecting and preventing crime. For that reason, video content analysis applications, either for real time (i.e. analytic) or post-event (i.e. forensic) analysis, have gained high interest in recent years. In this thesis, the primary focus is on two key aspects of video analysis, reliable moving object segmentation and carried object detection & identification. A novel moving object segmentation scheme by background subtraction is presented in this thesis. The scheme relies on
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Pacheco, Do Espirito Silva Caroline. "Feature extraction and selection for background modeling and foreground detection." Thesis, La Rochelle, 2017. http://www.theses.fr/2017LAROS005/document.

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Dans ce manuscrit de thèse, nous présentons un descripteur robuste pour la soustraction d’arrière-plan qui est capable de décrire la texture à partir d’une séquence d’images. Ce descripteur est moins sensible aux bruits et produit un histogramme court, tout en préservant la robustesse aux changements d’éclairage. Un autre descripteur pour la reconnaissance dynamique des textures est également proposé. Le descripteur permet d’extraire non seulement des informations de couleur, mais aussi des informations plus détaillées provenant des séquences vidéo. Enfin, nous présentons une approche de sélec
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Cordolino, Sobral Andrews. "Robust low-rank and sparse decomposition for moving object detection : from matrices to tensors." Thesis, La Rochelle, 2017. http://www.theses.fr/2017LAROS007/document.

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Dans ce manuscrit de thèse, nous introduisons les avancées récentes sur la décomposition en matrices (et tenseurs) de rang faible et parcimonieuse ainsi que les contributions pour faire face aux principaux problèmes dans ce domaine. Nous présentons d’abord un aperçu des méthodes matricielles et tensorielles les plus récentes ainsi que ses applications sur la modélisation d’arrière-plan et la segmentation du premier plan. Ensuite, nous abordons le problème de l’initialisation du modèle de fond comme un processus de reconstruction à partir de données manquantes ou corrompues. Une nouvelle méthod
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Dong, Pei. "Pixel domain and compressed domain video analysis for smart information extraction." Thesis, The University of Sydney, 2014. http://hdl.handle.net/2123/11952.

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Assisted consumption and manipulation of the rapidly expanding digital video archives has become one of the crucial topics in video analysis. This is mainly due to the inefficiency of traditional manual browsing, especially in face of the explosive amount of information. Therefore, extracting the salient information from videos in an automatic and smart way is a promising endeavour. In different scenarios, information extraction for videos can be defined in diversified ways. For the professionally edited genres, such as documentaries, movies and TV news, a condensed version with extracted part
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Molin, Joel. "Foreground Segmentation of Moving Objects." Thesis, Linköping University, Department of Electrical Engineering, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-52544.

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<p>Foreground segmentation is a common first step in tracking and surveillance applications.  The purpose of foreground segmentation is to provide later stages of image processing with an indication of where interesting data can be found.  This thesis is an investigation of how foreground segmentation can be performed in two contexts: as a pre-step to trajectory tracking and as a pre-step in indoor surveillance applications.</p><p>Three methods are selected and detailed: a single Gaussian method, a Gaussian mixture model method, and a codebook method.  Experiments are then performed on typical
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Arriaza, Barriga Romina Carolina. "Cycle-GAN for removing structured foreground objects in images." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-287536.

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The TRACAB Image Tracking System is used by ChyronHego for the tracking of ball and players on football fields. It requires the calibration of the cameras around the arena which is disrupted by fences and other mesh structures that are positioned between the camera and the field as a safety measure for the public. The purpose of this work was the implementation of a cycle consistent Generative Adversarial Network (cycle-GAN) for removing the fence from the image using unpaired data. Cycle-GANs are part of the state-of-the-art of image-to-image translation and can solve this kind of problem wit
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Books on the topic "Foreground object"

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Danielson, J. Taylor, and Robin Stryker. Cultural Influences on Social Policy Development. Edited by Daniel Béland, Kimberly J. Morgan, and Christopher Howard. Oxford University Press, 2014. http://dx.doi.org/10.1093/oxfordhb/9780199838509.013.032.

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Meaning-making is the core of all cultural mechanisms influencing policy development. Culture includes ideas; ideologies; values; concepts and theories; categories; beliefs; attitudes; opinions; norms; cognitive schema and paradigms; frames; discourse; spoken, written, or signed language; and any material object to which meaning is attached. Each shapes policies through meaning-making. This chapter explores how diverse aspects of culture play cognitive, normative-evaluative, and strategic roles in U.S. social policy development. It reviews exemplary research exploring the relationship between
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Fazel, Valerie M., and Louise Geddes, eds. Variable Objects. Edinburgh University Press, 2021. http://dx.doi.org/10.3366/edinburgh/9781474481397.001.0001.

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Drawing on new materialism and object-oriented ontology, this book proposes that Shakespeare is a vibrant object replete with a variable energy that accounts or its infinite meaning-making capacity. Using critical race theory, object-oriented feminism, performance studies, Global Shakespeares, media students and game theory, the collection’s essays explore the dialogical relations between the Shakespeare object and its appropriation. Instead of moving away from the source of appropriations, an object-oriented approach centralises Shakespeare without the constraints of outdate notions of fideli
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Morris, Pam. Worldly Realism. Edinburgh University Press, 2017. http://dx.doi.org/10.3366/edinburgh/9781474419130.003.0001.

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A preliminary discussion of Northanger Abbey and Jacob’s Room, foregrounds Austen’s and Woolf’s insistence upon non-heroic, unexceptional protagonists, the challenge their writing poses to existing genres and its disjunction from established, consensual interpretive systems. Jacques Ranciére’s concept of consensual and dissensual regimes of the perceptible, and recent accounts of the constitutive relationship of inanimate objects with self, provide a theoretical framework for discussing these experimental aspects of each writer’s work. The chapter maps an epistemological tradition linking thes
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Blakely, Sandra, ed. Gods, Objects, and Ritual Practice. Lockwood Press, 2017. http://dx.doi.org/10.5913/2017796.

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Conversations about materiality have helped forge a common meeting ground for scholars seeking to integrate images, sites, texts, and implements in their approach to religion in the ancient Mediterranean. The fourteen chapters in this volume explore the productivity of these approaches, with case studies from Israel, Athens, Rome, Sicily, and North Africa . The results foreground the capacity of material approaches to cast lighton the cultural creation of the sacred through the integration of rhetorical,material, and iconographic means. They open more nuanced pathways to theuses of text in the
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Simon, Julia. Time, Tradition, Performance, and the Aesthetic Object. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190666552.003.0006.

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The final chapter addresses the temporality of a genre based on tradition. Working from conceptions of tradition gleaned from the epic and historical chronicle, and of modern anxieties about the weight of the past, reveals a resonating, vibrant, multi-temporal field for the blues that employs meta-textual references to the tradition to create ironic distance. Tracing the genealogy of a riff from Robert Johnson’s “If I Had Possession Over Judgment Day” to Muddy Waters’s “Rollin’ and Tumblin’, ” through to Nick Moss and the Flip Tops’ “The Money I Make” reveals the dynamic forms of temporal simu
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Hohmann, Jessie, and Daniel Joyce, eds. International Law's Objects. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198798200.001.0001.

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International law’s rich existence in the world can be illuminated by its objects. International law is often developed, conveyed, and authorized through its objects and/or their representation. From the symbolic (the regalia of the head of state and the symbols of sovereignty), to the mundane (a can of dolphin-safe tuna certified as complying with international trade standards), international legal authority can be found in the objects around us. Similarly, the practice of international law often relies on material objects or their image, both as evidence (satellite images, bones of the victi
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Simon, Julia. Objects, Fragments, Scenes, and the Construction of Narrative. Oxford University Press, 2017. http://dx.doi.org/10.1093/acprof:oso/9780190666552.003.0005.

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This chapter interrogates the construction of narrative out of lyrical and musical fragments and scenes. Tracing displacements and condensations in the blues reveals a metonymic structure underpinning narrative articulations. Close examination of the contexts of reception—including the minstrel show, the juke joint, and most especially the print advertising of race record labels—unearths a system that guides listeners to construct narrative cohesion out of fragments and pieces. Analyzing Charley Patton’s “High Water Everywhere,” Blind Lemon Jefferson’s “Competition Bed Blues,” and Robert Johns
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Carruthers, Janice, Mairi McLaughlin, and Olivia Walsh, eds. Historical and Sociolinguistic Approaches to French. Oxford University PressOxford, 2024. http://dx.doi.org/10.1093/oso/9780192894366.001.0001.

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Abstract Historical and Sociolinguistic Approaches to French showcases the most innovative research being done today on both the history and the sociolinguistics of the French language. It foregrounds in particular current research at the intersection of these two fields in historical sociolinguistics, a field which has seen significant recent growth. The research in the volume is all strongly data-centred, drawing on a wide range of both well-established and innovative theoretical and methodological approaches in order to open up new perspectives on the study of the French language in the twe
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Masuda, Takahiko, Liman Man Wai Li, and Matthew J. Russell. Judging the World Dialectically versus Non-Dialectically. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780199348541.003.0007.

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For over three decades, cultural psychologists have advocated the importance of cultural meaning systems and their effects on basic modes of perception and cognition. This chapter reviews findings which have demonstrated that culturally dominant ways of thinking influence people’s basic perceptual and cognitive processes: East Asians are more likely to endorse holistic thinking and dialectical thinking style when they process information, such that they incorporate more contextual information into their judgments of focal objects, and North Americans are more likely to endorse non-dialectical
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Schlarb, Damien B. Melville's Wisdom. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780197585566.001.0001.

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This book explores the manner in which Herman Melville responds to the spiritual crisis of modernity by using the language of the biblical Old Testament wisdom books to moderate contemporary discourses on religion, skepticism, and literature. Melville’s work is an example of how romantic literature fills the interpretive lacuna left by contemporary theology. This book argues that attending to Melville’s engagement with the wisdom books (Job, Proverbs, and Ecclesiastes) can help us understand a paradox at the heart of American modernity: the simultaneous displacement and affirmation of biblical
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Book chapters on the topic "Foreground object"

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Sullivan, Josephine, Andrew Blake, and Jens Rittscher. "Statistical Foreground Modelling for Object Localisation." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-45053-x_20.

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Li, Boren, Po-Yu Zhuang, Jian Gu, Mingyang Li, and Ping Tan. "Interpretable Foreground Object Search as Knowledge Distillation." In Computer Vision – ECCV 2020. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58604-1_12.

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Dragonas, John, Anastasios Doulamis, George Miaoulis, and Dimitri Plemenos. "Collaborative Foreground Background Object Isolation and Tracking." In Intelligent Computer Graphics 2010. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15690-8_4.

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Chen, Jifei, Yafei Zhang, Yulong Tian, and Jianjiang Lu. "An Object Recognition Strategy Base upon Foreground Detection." In Artificial Intelligence and Computational Intelligence. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23896-3_5.

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Maddalena, Lucia, and Alfredo Petrosino. "Multivalued Background/Foreground Separation for Moving Object Detection." In Fuzzy Logic and Applications. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02282-1_33.

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Yang, Zongxin, Yunchao Wei, and Yi Yang. "Collaborative Video Object Segmentation by Foreground-Background Integration." In Computer Vision – ECCV 2020. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58558-7_20.

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Zhu, Zhenyue, Shujing Lyu, Xiao Tu, and Yue Lu. "Object Detection Based on Sparse Representation of Foreground." In Pattern Recognition and Artificial Intelligence. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59830-3_40.

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Wang, Yubin, and Junyong Zhai. "Highway Abandoned Object Detection Based on Foreground Extraction." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-6847-3_31.

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Srihari, P., and Harikiran Jonnadula. "Object Detection and Foreground Extraction in Thermal Images." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4831-2_57.

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Sun, Fengming, Lufei Huang, Xia Yuan, and Chunxia Zhao. "Foreground-Background Collaboration Network for Salient Object Detection." In Lecture Notes in Computer Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-02375-0_16.

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Conference papers on the topic "Foreground object"

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Liu, Guangyang, Zhongjin Li, and Hidetoshi Ando. "Foreground Probability Enhancement for Accurate Underwater Object Detection." In 2025 6th International Conference on Computer Vision, Image and Deep Learning (CVIDL). IEEE, 2025. https://doi.org/10.1109/cvidl65390.2025.11085788.

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Zhang, Chenxi, Qing Zhang, and Jiayun Wu. "Rethinking Camouflaged Object Detection via Foreground-Background Interactive Learning." In ICASSP 2025 - 2025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2025. https://doi.org/10.1109/icassp49660.2025.10889016.

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Ci, Wenyan, Yangxun Ge, Lu Tian, Hongyi Hou, and Jihua Ma. "Road foreground small object detection algorithm based on improved YOLOv5s." In Sixteenth International Conference on Digital Image Processing (ICDIP 2024), edited by Zhaohui Wang, Jindong Tian, and Mrinal Mandal. SPIE, 2024. http://dx.doi.org/10.1117/12.3037163.

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Zhao, Yinan, Brian Price, Scott Cohen, and Danna Gurari. "Unconstrained Foreground Object Search." In 2019 IEEE/CVF International Conference on Computer Vision (ICCV). IEEE, 2019. http://dx.doi.org/10.1109/iccv.2019.00212.

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Huang, Yea-Shuan, and Fang-Hsuan Cheng. "Object-Oriented Foreground Image Extraction." In Second International Conference on Innovative Computing, Informatio and Control (ICICIC 2007). IEEE, 2007. http://dx.doi.org/10.1109/icicic.2007.413.

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Zhu, Junguang. "Foreground Object Segmentation with Objectness Measure." In The fourth International Conference on Information Science and Cloud Computing. Sissa Medialab, 2016. http://dx.doi.org/10.22323/1.264.0039.

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Zhu, Hengliang, Bin Sheng, Xiao Lin, Yangyang Hao, and Lizhuang Ma. "Foreground Object Sensing for Saliency Detection." In ICMR'16: International Conference on Multimedia Retrieval. ACM, 2016. http://dx.doi.org/10.1145/2911996.2912008.

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Rosenfeld, Amir, and Daphna Weinshall. "Extracting foreground masks towards object recognition." In 2011 IEEE International Conference on Computer Vision (ICCV). IEEE, 2011. http://dx.doi.org/10.1109/iccv.2011.6126391.

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Kulkarni, Mandar, and A. N. Rajagopalan. "Tensor Voting Based Foreground Object Extraction." In 2011 Third National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG). IEEE, 2011. http://dx.doi.org/10.1109/ncvpripg.2011.27.

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10

Fu, Huazhu, Dong Xu, Bao Zhang, and Stephen Lin. "Object-Based Multiple Foreground Video Co-segmentation." In 2014 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2014. http://dx.doi.org/10.1109/cvpr.2014.405.

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