Learning Action Primitives for Multi-level Video Event Understanding PDF Download
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Author: Erhunzi
Publisher:
ISBN:
Category :
Languages : en
Pages : 33
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Book Description
Human action categories exhibit significant intra-class variation. Changes in viewpoint, human appearance, and the temporal evolution of an action confound recognition algorithms. In order to address this, we present an approach to discover action primitives, sub-categoriesof action classes, that allow us to model this intra-class variation. We learn action primitives and their interrelations in a multi-level spatio-temporal model for action recognition. Action primitives are discovered via a data-driven clustering approach that focuses on repeatable,discriminative sub-categories. Higher-level interactions between action primitives and the actions of a set of people present in a scene are learned. Empirical results demonstrate that these action primitives can be effectively localized, and using them to model action classesimproves action recognition performance on challenging datasets.
Author: Erhunzi
Publisher:
ISBN:
Category :
Languages : en
Pages : 33
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Book Description
Human action categories exhibit significant intra-class variation. Changes in viewpoint, human appearance, and the temporal evolution of an action confound recognition algorithms. In order to address this, we present an approach to discover action primitives, sub-categoriesof action classes, that allow us to model this intra-class variation. We learn action primitives and their interrelations in a multi-level spatio-temporal model for action recognition. Action primitives are discovered via a data-driven clustering approach that focuses on repeatable,discriminative sub-categories. Higher-level interactions between action primitives and the actions of a set of people present in a scene are learned. Empirical results demonstrate that these action primitives can be effectively localized, and using them to model action classesimproves action recognition performance on challenging datasets.
Author: Lei Chen
Publisher:
ISBN:
Category :
Languages : en
Pages : 33
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Book Description
Human action categories exhibit significant intra-class variation. Changes in viewpoint, human appearance, and the temporal evolution of an action confound recognition algorithms. In order to address this, we present an approach to discover action primitives, sub-categoriesof action classes, that allow us to model this intra-class variation. We learn action primitives and their interrelations in a multi-level spatio-temporal model for action recognition. Action primitives are discovered via a data-driven clustering approach that focuses on repeatable,discriminative sub-categories. Higher-level interactions between action primitives and the actions of a set of people present in a scene are learned. Empirical results demonstrate that these action primitives can be effectively localized, and using them to model action classesimproves action recognition performance on challenging datasets.
Author: Lourdes Agapito
Publisher: Springer
ISBN: 3319161997
Category : Computers
Languages : en
Pages : 872
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Book Description
The four-volume set LNCS 8925, 8926, 8927 and 8928 comprises the thoroughly refereed post-workshop proceedings of the Workshops that took place in conjunction with the 13th European Conference on Computer Vision, ECCV 2014, held in Zurich, Switzerland, in September 2014. The 203 workshop papers were carefully reviewed and selected for inclusion in the proceedings. They where presented at workshops with the following themes: where computer vision meets art; computer vision in vehicle technology; spontaneous facial behavior analysis; consumer depth cameras for computer vision; "chalearn" looking at people: pose, recovery, action/interaction, gesture recognition; video event categorization, tagging and retrieval towards big data; computer vision with local binary pattern variants; visual object tracking challenge; computer vision + ontology applies cross-disciplinary technologies; visual perception of affordance and functional visual primitives for scene analysis; graphical models in computer vision; light fields for computer vision; computer vision for road scene understanding and autonomous driving; soft biometrics; transferring and adapting source knowledge in computer vision; surveillance and re-identification; color and photometry in computer vision; assistive computer vision and robotics; computer vision problems in plant phenotyping; and non-rigid shape analysis and deformable image alignment. Additionally, a panel discussion on video segmentation is included.
Author: Alberto Amato
Publisher: Springer Science & Business Media
ISBN: 1461454859
Category : Computers
Languages : en
Pages : 111
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Book Description
Semantic Analysis and Understanding of Human Behaviour in Video Streaming investigates the semantic analysis of the human behaviour captured by video streaming, and introduces both theoretical and technological points of view. Video analysis based on the semantic content is in fact still an open issue for the computer vision research community, especially when real-time analysis of complex scenes is concerned. This book explores an innovative, original approach to human behaviour analysis and understanding by using the syntactical symbolic analysis of images and video streaming described by means of strings of symbols. A symbol is associated to each area of the analyzed scene. When a moving object enters an area, the corresponding symbol is appended to the string describing the motion. This approach allows for characterizing the motion of a moving object with a word composed by symbols. By studying and classifying these words we can categorize and understand the various behaviours. The main advantage of this approach lies in the simplicity of the scene and motion descriptions so that the behaviour analysis will have limited computational complexity due to the intrinsic nature both of the representations and the related operations used to manipulate them. Besides, the structure of the representations is well suited for possible parallel processing, thus allowing for speeding up the analysis when appropriate hardware architectures are used. A new methodology for design systems for hierarchical high semantic level analysis of video streaming in narrow domains is also proposed. Guidelines to design your own system are provided in this book. Designed for practitioners, computer scientists and engineers working within the fields of human computer interaction, surveillance, image processing and computer vision, this book can also be used as secondary text book for advanced-level students in computer science and engineering.
Author: Huimin Lu
Publisher: Springer Nature
ISBN: 303056178X
Category : Technology & Engineering
Languages : en
Pages : 265
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Book Description
This book provides insights into research in the field of artificial intelligence in combination with robotics technologies. The integration of artificial intelligence and robotic technologies is a highly topical area for researchers and developers from academia and industry around the globe, and it is likely that artificial intelligence will become the main approach for the next generation of robotics research. The tremendous number of artificial intelligence algorithms and big data solutions has significantly extended the range of potential applications for robotic technologies, and has also brought new challenges for the artificial intelligence community. Sharing recent advances in the field, the book features papers by young researchers presented at the 4th International Symposium on Artificial Intelligence and Robotics 2019 (ISAIR2019), held in Daegu, Korea, on August 20–24, 2019.
Author: Thomas F. Shipley
Publisher: Oxford University Press
ISBN: 0198040709
Category : Psychology
Languages : en
Pages : 733
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Book Description
We effortlessly recognize all sorts of events--from simple events like people walking to complex events like leaves blowing in the wind. We can also remember and describe these events, and in general, react appropriately to them, for example, in avoiding an approaching object. Our phenomenal ease interacting with events belies the complexity of the underlying processes we use to deal with them. Driven by an interest in these complex processes, research on event perception has been growing rapidly. Events are the basis of all experience, so understanding how humans perceive, represent, and act on them will have a significant impact on many areas of psychology. Unfortunately, much of the research on event perception--in visual perception, motor control, linguistics, and computer science--has progressed without much interaction. This volume is the first to bring together computational, neurological, and psychological research on how humans detect, classify, remember, and act on events. The book will provide professional and student researchers with a comprehensive collection of the latest research in these diverse fields.
Author: Shyamal Deep Buch
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
The visual world offers a smorgasbord of interesting events: human-object interactions, dynamic visual relationships, and activities of daily living. The ability to comprehend them is critical to the development of real-world, interactive AI systems. However, making sense of these events as humans do -- from a continuous and high-volume sensory stream in an efficient and effective manner -- remains a daunting endeavor. The challenges are chiefly two-fold. First, videos are computationally expensive to process; we need more than traditional extensions of systems designed for images. Second, videos capture a broad spectrum of event complexity, from low-level action primitives to higher-order spatiotemporal relationships; we need techniques to learn these semantics from natural language without expensive, dense annotations. This dissertation presents several research contributions aimed at addressing these challenges. First, we will discuss new architectures for recognizing actions in videos, which learn how to allocate a fixed computation budget to improve efficiency-accuracy by an order of magnitude over traditional techniques. Second, we will present new frameworks that advance our capability for efficiently learning about dense visual events from weak natural language supervision, including settings where language is not well-structured or contains ambiguous coreferences. Finally, we will discuss how a novel technique, leveraging progress in multimodal foundation models, reveals fundamental insights into pressing challenges and opportunities for deeper temporal event understanding with improved efficiency.
Author: Yu-Jin Zhang
Publisher: Springer Nature
ISBN: 9811558736
Category : Computers
Languages : en
Pages : 1963
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Book Description
Image techniques have been developed and implemented for various purposes, and image engineering (IE) is a rapidly evolving, integrated discipline comprising the study of all the different branches of image techniques, and encompassing mathematics, physics, biology, physiology, psychology, electrical engineering, computer science and automation. Advances in the field are also closely related to the development of telecommunications, biomedical engineering, remote sensing, surveying and mapping, as well as document processing and industrial applications. IE involves three related and partially overlapping groups of image techniques: image processing (IP) (in its narrow sense), image analysis (IA) and image understanding (IU), and the integration of these three groups makes the discipline of image engineering an important part of the modern information era. This is the first handbook on image engineering, and provides a well-structured, comprehensive overview of this new discipline. It also offers detailed information on the various image techniques. It is a valuable reference resource for R&D professional and undergraduate students involved in image-related activities.
Author: Kathy Hirsh-Pasek
Publisher: Oxford University Press
ISBN: 0199753717
Category : Language Arts & Disciplines
Languages : en
Pages : 605
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Book Description
Although there has been a surge in our understanding of children's vocabulary growth, theories of word learning lack a primary focus on verbs and adjectives. Researchers throughout the world recognize how our understanding of language acquisition can be at best partial if we cannot comprehend how verbs are learned. This volume represents a proliferation of research on the frontier of early verb learning, enhancing our understanding of the building blocks of language and considering new ways to assess key aspects of language growth.
Author: Myo Thida
Publisher: Springer Nature
ISBN: 3031022491
Category : Technology & Engineering
Languages : en
Pages : 8
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Book Description
Video context analysis is an active and vibrant research area, which provides means for extracting, analyzing and understanding behavior of a single target and multiple targets. Over the last few decades, computer vision researchers have been working to improve the accuracy and robustness of algorithms to analyse the context of a video automatically. In general, the research work in this area can be categorized into three major topics: 1) counting number of people in the scene 2) tracking individuals in a crowd and 3) understanding behavior of a single target or multiple targets in the scene. This book focusses on tracking individual targets and detecting abnormal behavior of a crowd in a complex scene. Firstly, this book surveys the state-of-the-art methods for tracking multiple targets in a complex scene and describes the authors' approach for tracking multiple targets. The proposed approach is to formulate the problem of multi-target tracking as an optimization problem of finding dynamic optima (pedestrians) where these optima interact frequently. A novel particle swarm optimization (PSO) algorithm that uses a set of multiple swarms is presented. Through particles and swarms diversification, motion prediction is introduced into the standard PSO, constraining swarm members to the most likely region in the search space. The social interaction among swarm and the output from pedestrians-detector are also incorporated into the velocity-updating equation. This allows the proposed approach to track multiple targets in a crowded scene with severe occlusion and heavy interactions among targets. The second part of this book discusses the problem of detecting and localising abnormal activities in crowded scenes. We present a spatio-temporal Laplacian Eigenmap method for extracting different crowd activities from videos. This method learns the spatial and temporal variations of local motions in an embedded space and employs representatives of different activities to construct the model which characterises the regular behavior of a crowd. This model of regular crowd behavior allows for the detection of abnormal crowd activities both in local and global context and the localization of regions which show abnormal behavior.
