Performance Evaluation Of A Tracking Algorithm Including Attribute Data
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Performance Evaluation Of A Tracking Algorithm Including Attribute Data
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Author : Jean Dezert
language : en
Publisher: Infinite Study
Release Date :
Performance Evaluation Of A Tracking Algorithm Including Attribute Data written by Jean Dezert and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
The main objective of this work is to investigate the impact of the quality of attribute data source on the performance of a target tracking algorithm. An array of dense scenarios arranged according to the distance between closely spaced targets is studied by different confusion matrices.
Performance Valuation Of Racking Lgorithm Incorporating Attribute Data Processing Via Dsmt1
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Author : J. Dezert
language : en
Publisher: Infinite Study
Release Date :
Performance Valuation Of Racking Lgorithm Incorporating Attribute Data Processing Via Dsmt1 written by J. Dezert and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
The main objective of this paper is to investigate the impact of the quality of attribute data source on the performance of a target tracking algorithm. An array of dense scenarios arranged according to the distance between closely spaced targets is studied by different confusion matrices. The used algorithm is Generalized Data Association (GDA-MTT) algorithm for multiple target tracking processing kinematic as well as attribute data. The fusion rule for attribute data is based on Dezert-Smarandache Theory (DSmT).
Multitarget Tracking In Clutter Based On Generalized Data Association Performance Evaluation Of Fusion Rules
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Author : J. Dezert
language : en
Publisher: Infinite Study
Release Date :
Multitarget Tracking In Clutter Based On Generalized Data Association Performance Evaluation Of Fusion Rules written by J. Dezert and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
The objective of this chapter is to present and compare different fusion rules which can be used for Generalized Data Association (GDA) for multitarget tracking (MTT) in clutter.
Performance Evaluation Of Multitarget Tracking Algorithms
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Author : Huimin Chen
language : en
Publisher:
Release Date : 2002
Performance Evaluation Of Multitarget Tracking Algorithms written by Huimin Chen and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with categories.
Advances And Applications Of Dsmt For Information Fusion Vol 3
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Author : Florentin Smarandache
language : en
Publisher: Infinite Study
Release Date : 2004
Advances And Applications Of Dsmt For Information Fusion Vol 3 written by Florentin Smarandache and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Science categories.
This volume has about 760 pages, split into 25 chapters, from 41 contributors. First part of this book presents advances of Dezert-Smarandache Theory (DSmT) which is becoming one of the most comprehensive and flexible fusion theory based on belief functions. It can work in all fusion spaces: power set, hyper-power set, and super-power set, and has various fusion and conditioning rules that can be applied depending on each application. Some new generalized rules are introduced in this volume with codes for implementing some of them. For the qualitative fusion, the DSm Field and Linear Algebra of Refined Labels (FLARL) is proposed which can convert any numerical fusion rule to a qualitative fusion rule. When one needs to work on a refined frame of discernment, the refinement is done using Smarandache¿s algebraic codification. New interpretations and implementations of the fusion rules based on sampling techniques and referee functions are proposed, including the probabilistic proportional conflict redistribution rule. A new probabilistic transformation of mass of belief is also presented which outperforms the classical pignistic transformation in term of probabilistic information content. The second part of the book presents applications of DSmT in target tracking, in satellite image fusion, in snow-avalanche risk assessment, in multi-biometric match score fusion, in assessment of an attribute information retrieved based on the sensor data or human originated information, in sensor management, in automatic goal allocation for a planetary rover, in computer-aided medical diagnosis, in multiple camera fusion for tracking objects on ground plane, in object identification, in fusion of Electronic Support Measures allegiance report, in map regenerating forest stands, etc.
Generalized Data Association For Multitarget Tracking In Clutter
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Author : A. Tchamova
language : en
Publisher: Infinite Study
Release Date :
Generalized Data Association For Multitarget Tracking In Clutter written by A. Tchamova and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
The objective of this chapter is to present an approach for target track ing in cluttered environment, which incorporates the advanced concept of generalized data (kinematics and attribute) association (GDA) to improve track maintenance performance in complicated situations (closely spaced and/or crossing targets), when kinematics data are insufficient for correct decision making.
A Summary Of Research 1995
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Author : United States. Naval Postgraduate School, Monterey, CA.
language : en
Publisher:
Release Date : 1995
A Summary Of Research 1995 written by United States. Naval Postgraduate School, Monterey, CA. and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Military research categories.
Pattern Recognition And Computer Vision
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Author : Yuxin Peng
language : en
Publisher: Springer Nature
Release Date : 2020-10-14
Pattern Recognition And Computer Vision written by Yuxin Peng and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-14 with Computers categories.
The three-volume set LNCS 12305, 12306, and 12307 constitutes the refereed proceedings of the Third Chinese Conference on Pattern Recognition and Computer Vision, PRCV 2020, held virtually in Nanjing, China, in October 2020. The 158 full papers presented were carefully reviewed and selected from 402 submissions. The papers have been organized in the following topical sections: Part I: Computer Vision and Application, Part II: Pattern Recognition and Application, Part III: Machine Learning.
Sensor And Data Fusion
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Author : Lawrence A. Klein
language : en
Publisher: SPIE Press
Release Date : 2004
Sensor And Data Fusion written by Lawrence A. Klein and has been published by SPIE Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Technology & Engineering categories.
This book illustrates the benefits of sensor fusion by considering the characteristics of infrared, microwave, and millimeter-wave sensors, including the influence of the atmosphere on their performance. Applications that benefit from this technology include: vehicular traffic management, remote sensing, target classification and tracking- weather forecasting- military and homeland defense. Covering data fusion algorithms in detail, Klein includes a summary of the information required to implement each of the algorithms discussed, and outlines system application scenarios that may limit sensor size but that require high resolution data.
Object Trackers Performance Evaluation And Improvement With Applications Using High Order Tensor
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Author : Yu Pang
language : en
Publisher:
Release Date : 2020
Object Trackers Performance Evaluation And Improvement With Applications Using High Order Tensor written by Yu Pang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Visual tracking is one of the fundamental problems in computer vision. This topic has been a widely explored area attracting a great amount of research efforts. Over the decades, hundreds of visual tracking algorithms, or trackers in short, have been developed and a great packs of public datasets are available alongside. As the number of trackers grow, it then becomes a common problem how to evaluate who is a better tracker. Many metrics have been proposed together with tons of evaluation datasets. In my research work, we first make an application practice of tracking multiple objects in a restricted scene with very low frame rate. It has a unique challenge that the image quality is low and we cannot assume images are close together in a temporal space. We design a framework that utilize background subtraction and object detection, then we apply template matching algorithms to achieve the tracking by detection. While we are exploring the applications of tracking algorithm, we realize the problem when authors compare their proposed tracker with others, there is unavoidable subjective biases: it is non-trivial for the authors to optimize other trackers, while they can reasonably tune their own tracker to the best. Our assumption is based on that the authors will give a default setting to other trackers, hence the performances of other trackers are less biased. So we apply a leave-their-own-tracker-out strategy to weigh the performances of other different trackers. we derive four metrics to justify the results. Besides the biases in evaluation, the datasets we use as ground truth may not be perfect either. Because all of them are labeled by human annotators, they are prone to label errors, especially due to partial visibility and deformation. we demonstrate some human errors from existing datasets and propose smoothing technologies to detect and correct them. we use a two-step adaptive image alignment algorithm to find the canonical view of the video sequence. then use different techniques to smooth the trajectories at certain degrees. The results show it can slightly improve the trained model, but would overt if overcorrected. Once we have a clear understanding and reasonable approaches towards the visual tracking scenario, we apply the principles in multi-target tracking cases. To solve the problem, we formulate it into a multi-dimensional assignment problem, and build the motion information in a high-order tensor framework. We propose to solve it using rank-1 tensor approximation and use a tensor power iteration algorithm to efficiently obtain the solution. It can apply in pedestrian tracking, aerial video tracking, as well as curvalinear structure tracking in medical video. Furthermore, this proposed framework can also fit into the affinity measurement of multiple objects simultaneously. We propose the Multiway Histogram Intersection to obtain the similarities between histograms of more than two targets. With the solution of using tensor power iteration algorithm, we show it can be applied in a few multi-target tracking applications.