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Tracking Chapter from the book "Computer Vision: A Modern Approach"

Computer Vision Central - Posted on November 29, 2011 at 10:27 pm. Updated on November 29, 2011 at 10:41 pm.

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  • Contents
    1 Tracking 2
    1.1 Tracking by Detection
    1.1.1 Tracking Multiple Objects with Unreliable Detectors
    1.1.2 Matching Small Image Patches
    1.2 Tracking using Matching
    1.2.1 Matching Summary Representations
    1.2.2 Matching and Flow
    1.2.3 Tracking using Flow
    1.3 Tracking with Probability
    1.3.1 Linear Measurements and Linear Dynamics 
    1.3.2 The Kalman Filter
    1.3.3 Forward–Backward Smoothing
    1.4 Data Association
    1.4.1 Linking Kalman Filters with Detection Methods
    1.4.2 Key Methods of Data Association
    1.5 Particle Filtering
    1.5.1 Multiple Modes
    1.5.2 Sampled Representations of Probability Distributions
    1.5.3 The Simplest Particle Filter
    1.5.4 A Workable Particle Filter 
    1.5.5 If’s, And’s and But’s — Practical Issues in Building Particle
    Filters
    1.6 Notes
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