Occlusions And Their Role In Object Detection In Video
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Occlusions And Their Role In Object Detection In Video
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Author : Alper Ayvaci
language : en
Publisher:
Release Date : 2012
Occlusions And Their Role In Object Detection In Video written by Alper Ayvaci and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.
Occlusions and disocclusions are essential cues for human perception in understanding the layout of a scene. By analyzing how some parts of the scene go out of the sight (occluded) and new parts appear (disoccluded), one can infer the topology of the objects in it. Since the scene geometry and its dynamics induce this phenomena, they are fundamental cues in computer vision and video processing tasks such as visual exploration, object recognition, activity recognition, tracking and video compression. In this thesis, we first introduce three methods to detect occlusions in an image sequence: (1) a motion segmentation algorithm which partitions an oversegmented image into two parts: a region on which optical flow is expressed with a piecewise-constant field and occluded regions where flow is not defined, (2) an optical flow estimation method which additionally detects occlusions modeling them as sparse subset of the image domain, and (3) a saliency detection algorithm which detects the parts of the image domain whose motion is inconsistent with the camera motion. In the second part of the thesis, we show that the problem of object detection in a video can be cast as an unsupervised segmentation scheme using occlusion cues and solved using convex optimization for an unknown number and geometry of objects in the scene. We further extend this approach by incorporating semantic priors for object categories that are learned from object recognition datasets. This enables the detection algorithm to segment and categorize objects jointly.
Moving Object Detection Based On Background Subtraction Under Cwt Domain For Video Surveillance System
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Author : Chandra Shaker Arrabotu
language : en
Publisher: Archers & Elevators Publishing House
Release Date :
Moving Object Detection Based On Background Subtraction Under Cwt Domain For Video Surveillance System written by Chandra Shaker Arrabotu and has been published by Archers & Elevators Publishing House this book supported file pdf, txt, epub, kindle and other format this book has been release on with Antiques & Collectibles categories.
Occlusion Detection And Edge Processing In A Correlation Based Object Tracker
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Author : Neilesh R. Patel
language : en
Publisher:
Release Date : 1994
Occlusion Detection And Edge Processing In A Correlation Based Object Tracker written by Neilesh R. Patel and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994 with categories.
Multiple Object Tracking With Occlusion Handling
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Author : Murtaza Safri
language : en
Publisher:
Release Date : 2010
Multiple Object Tracking With Occlusion Handling written by Murtaza Safri and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.
Object tracking is an important problem with wide ranging applications. The purpose is to detect object contours and track their motion in a video. Issues of concern are to be able to map objects correctly between two frames, and to be able to track through occlusion. This thesis discusses a novel framework for the purpose of object tracking which is inspired from image registration and segmentation models.
Occlusion Reasoning For Multiple Object Visual Tracking
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Author : Zheng Wu
language : en
Publisher:
Release Date : 2013
Occlusion Reasoning For Multiple Object Visual Tracking written by Zheng Wu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.
Abstract: Occlusion reasoning for visual object tracking in uncontrolled environments is a challenging problem. It becomes significantly more difficult when dense groups of indistinguishable objects are present in the scene that cause frequent inter-object interactions and occlusions. We present several practical solutions that tackle the inter-object occlusions for video surveillance applications. In particular, this thesis proposes three methods. First, we propose "reconstruction-tracking," an online multi-camera spatial-temporal data association method for tracking large groups of objects imaged with low resolution. As a variant of the well-known Multiple-Hypothesis-Tracker, our approach localizes the positions of objects in 3D space with possibly occluded observations from multiple camera views and performs temporal data association in 3D. Second, we develop "track linking," a class of offline batch processing algorithms for long-term occlusions, where the decision has to be made based on the observations from the entire tracking sequence. We construct a graph representation to characterize occlusion events and propose an efficient graph-based/combinatorial algorithm to resolve occlusions. Third, we propose a novel Bayesian framework where detection and data association are combined into a single module and solved jointly. Almost all traditional tracking systems address the detection and data association tasks separately in sequential order. Such a design implies that the output of the detector has to be reliable in order to make the data association work. Our framework takes advantage of the often complementary nature of the two subproblems, which not only avoids the error propagation issue from which traditional "detection-tracking approaches" suffer but also eschews common heuristics such as "non-maximum suppression" of hypotheses by modeling the likelihood of the entire image. The thesis describes a substantial number of experiments, involving challenging, notably distinct simulated and real data, including infrared and visible-light data sets recorded ourselves or taken from data sets publicly available. In these videos, the number of objects ranges from a dozen to a hundred per frame in both monocular and multiple views. The experiments demonstrate that our approaches achieve results comparable to those of state-of-the-art approaches.
Computer Vision Eccv 2014
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Author : David Fleet
language : en
Publisher: Springer
Release Date : 2014-08-14
Computer Vision Eccv 2014 written by David Fleet and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-14 with Computers categories.
The seven-volume set comprising LNCS volumes 8689-8695 constitutes the refereed proceedings of the 13th European Conference on Computer Vision, ECCV 2014, held in Zurich, Switzerland, in September 2014. The 363 revised papers presented were carefully reviewed and selected from 1444 submissions. The papers are organized in topical sections on tracking and activity recognition; recognition; learning and inference; structure from motion and feature matching; computational photography and low-level vision; vision; segmentation and saliency; context and 3D scenes; motion and 3D scene analysis; and poster sessions.
Granular Video Computing With Rough Sets Deep Learning And In Iot
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Author : Debarati Bhunia Chakraborty
language : en
Publisher: World Scientific
Release Date : 2021-02-04
Granular Video Computing With Rough Sets Deep Learning And In Iot written by Debarati Bhunia Chakraborty and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-04 with Computers categories.
This volume links the concept of granular computing using deep learning and the Internet of Things to object tracking for video analysis. It describes how uncertainties, involved in the task of video processing, could be handled in rough set theoretic granular computing frameworks. Issues such as object tracking from videos in constrained situations, occlusion/overlapping handling, measuring of the reliability of tracking methods, object recognition and linguistic interpretation in video scenes, and event prediction from videos, are the addressed in this volume. The book also looks at ways to reduce data dependency in the context of unsupervised (without manual interaction/ labeled data/ prior information) training.This book may be used both as a textbook and reference book for graduate students and researchers in computer science, electrical engineering, system science, data science, and information technology, and is recommended for both students and practitioners working in computer vision, machine learning, video analytics, image analytics, artificial intelligence, system design, rough set theory, granular computing, and soft computing.
Leveraging Occlusion Cues For Causal Video Object Segmentation
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Author : Brian Taylor
language : en
Publisher:
Release Date : 2016
Leveraging Occlusion Cues For Causal Video Object Segmentation written by Brian Taylor and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
This thesis describes a framework leveraging occlusions as a cue for detecting objects and accurately localizing their boundaries throughout the course of a video. Triggered by the motion of objects in the scene, occlusions provide coarse knowledge of the spatial relationship of objects with respect to the viewer. While effective for detecting objects when motion is sufficient, we explore ways to reliably detect and track objects when motion is inadequate or difficult to estimate. In the first half, we incorporate semantic classifiers to provide cues when occlusions are weak, and observe occlusion and appearance information to be mutually beneficial, yielding results more resilient to failures of the component systems acting alone. Our system is evaluated on the semantic segmentation task. In the latter half, we drop semantics and instead devise a causal framework integrating segmentation results and occlusion cues from frames processed in the past. So long as objects move sufficiently with respect to the viewer at some point, they will be detected and subsequently tracked for the rest of the video. We evaluated our approach on the video object segmentation problem. The resulting system has the capability to automatically discover objects from occlusions in video and track their shapes as they evolve over time. Coarse depth is provided as a byproduct and the assignment of semantic category labels can be integrated in a natural way.
Emerging Trends In Expert Applications And Security
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Author : Vijay Singh Rathore
language : en
Publisher: Springer
Release Date : 2018-11-19
Emerging Trends In Expert Applications And Security written by Vijay Singh Rathore and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-11-19 with Technology & Engineering categories.
The book covers current developments in the field of expert applications and security, which employ advances of next-generation communication and computational technology to shape real-world applications. It gathers selected research papers presented at the ICETEAS 2018 conference, which was held at Jaipur Engineering College and Research Centre, Jaipur, India, on February 17–18, 2018. Key topics covered include expert applications and artificial intelligence; information and application security; advanced computing; multimedia applications in forensics, security and intelligence; and advances in web technologies: implementation and security issues.
Tracking Of Moving Objects In Video Sequences
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Author : S R Boselin Prabhu
language : en
Publisher: Educreation Publishing
Release Date : 2018-09-10
Tracking Of Moving Objects In Video Sequences written by S R Boselin Prabhu and has been published by Educreation Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-10 with Education categories.
Object tracking could be a terribly difficult task within the presence of variability illumination condition, background motion, complicated object form, partial and full object occlusions. The main intention of an object trailer is to make the path of an object over time by characteristic its position in all frames of the video. This book is intended to educate the researchers in the field of tracking of moving object(s) in a video sequence. This book provides a path for the researchers to identify the works done by others in the same field and thereby to figure out the gap in the current knowledge. This book is organized into three Modules. Module 1 talks about the introduction of object detection and tracking. Module 2 discusses about the various studies of object tracking and motion detection. The views of the various authors about this hot research topic are discussed in this Module and Module 3 gives the conclusion of the entire research review.Object tracking could be a terribly difficult task within the presence of variability illumination condition, background motion, complicated object form, partial and full object occlusions. The main intention of an object trailer is to make the path of an object over time by characteristic its position in all frames of the video. This book is intended to educate the researchers in the field of tracking of moving object(s) in a video sequence. This book provides a path for the researchers to identify the works done by others in the same field and thereby to figure out the gap in the current knowledge. This book is organized into three Modules. Module 1 talks about the introduction of object detection and tracking. Module 2 discusses about the various studies of object tracking and motion detection. The views of the various authors about this hot research topic are discussed in this Module and Module 3 gives the conclusion of the entire research review.