Model-based Visual Tracking: The OpenTL Framework

Author:   Giorgio Panin
Publisher:   John Wiley and Sons Ltd
ISBN:  

9780470876138


Pages:   318
Publication Date:   10 May 2011
Format:   Hardback
Availability:   In Print   Availability explained
Limited stock is available. It will be ordered for you and shipped pending supplier's limited stock.

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Model-based Visual Tracking: The OpenTL Framework


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Full Product Details

Author:   Giorgio Panin
Publisher:   John Wiley and Sons Ltd
Imprint:   Wiley-Blackwell
Dimensions:   Width: 16.40cm , Height: 2.20cm , Length: 24.50cm
Weight:   0.638kg
ISBN:  

9780470876138


ISBN 10:   0470876131
Pages:   318
Publication Date:   10 May 2011
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Out of Print
Availability:   In Print   Availability explained
Limited stock is available. It will be ordered for you and shipped pending supplier's limited stock.

Table of Contents

Preface. 1 Introduction . 1.1 Overview of the Problem. 1.2 General Tracking System Prototype. 1.3 The Tracking Pipeline. 2 Model Representation. 2.1 Camera Model. 2.2 Object Model. 2.3 Mapping Between Object and Sensor Spaces. 2.4 Object Dynamics. 3 The Visual Modality Abstraction. 3.1 Preprocessing. 3.2 Sampling and Updating Reference Features. 3.3 Model Matching with the Image Data. 3.4 Data Fusion Across Multiple Modalities and Cameras. 4 Examples of Visual Modalities. 4.1 Color Statistics. 4.2 Background Subtraction. 4.3 Blobs. 4.4 Model Contours. 4.5 Keypoints. 4.6 Motion. 4.7 Templates. 5 Recursive State-Space Estimation. 5.1 Target-State Distribution. 5.2 MLE and MAP Estimation. 5.3 Gaussian Filters. 5.4 Monte Carlo Filters. 5.5 Grid Filters. 6 Examples of Target Detectors. 6.1 Blob Clustering. 6.2 AdaBoost Classifiers. 6.3 Geometric Hashing. 6.4 Monte Carlo sampling. 6.5 Invariant Keypoints. 7 Building Applications with OpenTL. 7.1 Functional Architecture of OpenTL. 7.2 Building a Tutorial Application with OpenTL. 7.3 Other Application Examples. Appendix A: Pose Estimation. A.1 Point Correspondences. A.2 Line Correspondences. A.3 Point and Line Correspondences. A.4 Computation of the Projective DLT Matrices. Appendix B: Pose Representations . B.1 Poses Without Rotation. B.2 Parametrizing Rotations. B.3 Poses with Rotation and Uniform Scale. B.4 Affinity. B.5 Poses with Rotation and Nonuniform Scale. B.6 General Homography: The DLT Algorithm. Nomenclature. Bibliography. Index.

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Author Information

Giorgio Panin, PhD , is an Assistant Professor at the Technical University of Munich. His research focuses on robotics and embedded systems, with an emphasis on computer vision and object tracking for human-machine interaction, robot manipulation, and navigation tasks.

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