Motion Supports Object Recognition
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Motion Supports Object Recognition
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Author : Steven R. Holloway
language : en
Publisher:
Release Date : 2011
Motion Supports Object Recognition written by Steven R. Holloway and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Color vision categories.
The present study explores the role of motion in the perception of form from dynamic occlusion, employing color to help isolate the contributions of both visual pathways. Although the cells that respond to color cues in the environment usually feed into the ventral stream, humans can perceive motion based on chromatic cues. The current study was designed to use grey, green, and red stimuli to successively limit the amount of information available to the dorsal stream pathway, while providing roughly equal information to the ventral system. Twenty-one participants identified shapes that were presented in grey, green, and red and were defined by dynamic occlusion. The shapes were then presented again in a static condition where the maximum occlusions were presented as before, but without motion. Results showed an interaction between the motion and static conditions in that when the speed of presentation increased, performance in the motion conditions became significantly less accurate than in the static conditions. The grey and green motion conditions crossed static performance at the same point, whereas the red motion condition crossed at a much slower speed. These data are consistent with a model of neural processing in which the main visual systems share information. Moreover, they support the notion that presenting stimuli in specific colors may help isolate perceptual pathways for scientific investigation. Given the potential for chromatic cues to target specific visual systems in the performance of dynamic object recognition, exploring these perceptual parameters may help our understanding of human visual processing.
Object Recognition Using Motion Information
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Author : Richard Laszlo Madarasz
language : en
Publisher:
Release Date : 1983
Object Recognition Using Motion Information written by Richard Laszlo Madarasz and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983 with Dissertations, Academic categories.
Motion History Images For Action Recognition And Understanding
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Author : Md. Atiqur Rahman Ahad
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-28
Motion History Images For Action Recognition And Understanding written by Md. Atiqur Rahman Ahad and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-28 with Computers categories.
Human action analysis and recognition is a relatively mature field, yet one which is often not well understood by students and researchers. The large number of possible variations in human motion and appearance, camera viewpoint, and environment, present considerable challenges. Some important and common problems remain unsolved by the computer vision community. However, many valuable approaches have been proposed over the past decade, including the motion history image (MHI) method. This method has received significant attention, as it offers greater robustness and performance than other techniques. This work presents a comprehensive review of these state-of-the-art approaches and their applications, with a particular focus on the MHI method and its variants.
Representations And Techniques For 3d Object Recognition And Scene Interpretation
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Author : Derek Hoiem
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2011
Representations And Techniques For 3d Object Recognition And Scene Interpretation written by Derek Hoiem and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Computers categories.
One of the grand challenges of artificial intelligence is to enable computers to interpret 3D scenes and objects from imagery. This book organizes and introduces major concepts in 3D scene and object representation and inference from still images, with a focus on recent efforts to fuse models of geometry and perspective with statistical machine learning. The book is organized into three sections: (1) Interpretation of Physical Space; (2) Recognition of 3D Objects; and (3) Integrated 3D Scene Interpretation. The first discusses representations of spatial layout and techniques to interpret physical scenes from images. The second section introduces representations for 3D object categories that account for the intrinsically 3D nature of objects and provide robustness to change in viewpoints. The third section discusses strategies to unite inference of scene geometry and object pose and identity into a coherent scene interpretation. Each section broadly surveys important ideas from cognitive science and artificial intelligence research, organizes and discusses key concepts and techniques from recent work in computer vision, and describes a few sample approaches in detail. Newcomers to computer vision will benefit from introductions to basic concepts, such as single-view geometry and image classification, while experts and novices alike may find inspiration from the book's organization and discussion of the most recent ideas in 3D scene understanding and 3D object recognition. Specific topics include: mathematics of perspective geometry; visual elements of the physical scene, structural 3D scene representations; techniques and features for image and region categorization; historical perspective, computational models, and datasets and machine learning techniques for 3D object recognition; inferences of geometrical attributes of objects, such as size and pose; and probabilistic and feature-passing approaches for contextual reasoning about 3D objects and scenes. Table of Contents: Background on 3D Scene Models / Single-view Geometry / Modeling the Physical Scene / Categorizing Images and Regions / Examples of 3D Scene Interpretation / Background on 3D Recognition / Modeling 3D Objects / Recognizing and Understanding 3D Objects / Examples of 2D 1/2 Layout Models / Reasoning about Objects and Scenes / Cascades of Classifiers / Conclusion and Future Directions
Human Motion Sensing And Recognition
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Author : Honghai Liu
language : en
Publisher: Springer
Release Date : 2017-05-11
Human Motion Sensing And Recognition written by Honghai Liu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-11 with Technology & Engineering categories.
This book introduces readers to the latest exciting advances in human motion sensing and recognition, from the theoretical development of fuzzy approaches to their applications. The topics covered include human motion recognition in 2D and 3D, hand motion analysis with contact sensors, and vision-based view-invariant motion recognition, especially from the perspective of Fuzzy Qualitative techniques. With the rapid development of technologies in microelectronics, computers, networks, and robotics over the last decade, increasing attention has been focused on human motion sensing and recognition in many emerging and active disciplines where human motions need to be automatically tracked, analyzed or understood, such as smart surveillance, intelligent human-computer interaction, robot motion learning, and interactive gaming. Current challenges mainly stem from the dynamic environment, data multi-modality, uncertain sensory information, and real-time issues. These techniques are shown to effectively address the above challenges by bridging the gap between symbolic cognitive functions and numerical sensing & control tasks in intelligent systems. The book not only serves as a valuable reference source for researchers and professionals in the fields of computer vision and robotics, but will also benefit practitioners and graduates/postgraduates seeking advanced information on fuzzy techniques and their applications in motion analysis.
Motion Time And Object Recognition
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Author : Taosheng Liu
language : en
Publisher:
Release Date : 2001
Motion Time And Object Recognition written by Taosheng Liu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with categories.
Moving Object Detection And Segmentation For Remote Aerial Video Surveillance
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Author : Teutsch, Michael
language : en
Publisher: KIT Scientific Publishing
Release Date : 2015-03-11
Moving Object Detection And Segmentation For Remote Aerial Video Surveillance written by Teutsch, Michael and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-11 with Electronic computers. Computer science categories.
Unmanned Aerial Vehicles (UAVs) equipped with video cameras are a flexible support to ensure civil and military safety and security. In this thesis, a video processing chain is presented for moving object detection in aerial video surveillance. A Track-Before-Detect (TBD) algorithm is applied to detect motion that is independent of the camera motion. Novel robust and fast object detection and segmentation approaches improve the baseline TBD and outperform current state-of-the-art methods.
Moving Object Detection Using Background Subtraction
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Author : Soharab Hossain Shaikh
language : en
Publisher: Springer
Release Date : 2014-06-20
Moving Object Detection Using Background Subtraction written by Soharab Hossain Shaikh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-20 with Computers categories.
This Springer Brief presents a comprehensive survey of the existing methodologies of background subtraction methods. It presents a framework for quantitative performance evaluation of different approaches and summarizes the public databases available for research purposes. This well-known methodology has applications in moving object detection from video captured with a stationery camera, separating foreground and background objects and object classification and recognition. The authors identify common challenges faced by researchers including gradual or sudden illumination change, dynamic backgrounds and shadow and ghost regions. This brief concludes with predictions on the future scope of the methods. Clear and concise, this brief equips readers to determine the most effective background subtraction method for a particular project. It is a useful resource for professionals and researchers working in this field.
Moving Objects Detection Using Machine Learning
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Author : Navneet Ghedia
language : en
Publisher: Springer Nature
Release Date : 2022-01-01
Moving Objects Detection Using Machine Learning written by Navneet Ghedia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-01 with Technology & Engineering categories.
This book shows how machine learning can detect moving objects in a digital video stream. The authors present different background subtraction approaches, foreground segmentation, and object tracking approaches to accomplish this. They also propose an algorithm that considers a multimodal background subtraction approach that can handle a dynamic background and different constraints. The authors show how the proposed algorithm is able to detect and track 2D & 3D objects in monocular sequences for both indoor and outdoor surveillance environments and at the same time, also able to work satisfactorily in a dynamic background and with challenging constraints. In addition, the shows how the proposed algorithm makes use of parameter optimization and adaptive threshold techniques as intrinsic improvements of the Gaussian Mixture Model. The presented system in the book is also able to handle partial occlusion during object detection and tracking. All the presented work and evaluations were carried out in offline processing with the computation done by a single laptop computer with MATLAB serving as software environment.
Spatio Temporal Signatures For Object Recognition
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Author : Quoc C. Vuong
language : en
Publisher:
Release Date : 2004
Spatio Temporal Signatures For Object Recognition written by Quoc C. Vuong and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Perception categories.