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Visual Features—From Early Concepts to Modern Computer Vision Read chapter Read first chapter

2013 | OriginalPaper | Chapter

4. Evaluating and Extending Trajectory Features for Activity Recognition

Authors : Ross Messing, Atousa Torabi, Aaron Courville, Chris Pal

Published in: Advanced Topics in Computer Vision

Publisher: Springer London

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Abstract

Trajectory features are a powerful new way to describe video data. By leveraging the spatio-temporal range and structure of trajectories, they improve activity recognition performance compared to systems based on fixed local spatio-temporal volumes. This chapter places them in context, compares a sparse, generative model of extended trajectories to a dense, discriminative model of local trajectories, and explores ways to extend the sparse system with new kinds of information.

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previous chapter Recognizing Human Actions by Using Effective Codebooks and Tracking
next chapter Co-recognition of Images and Videos: Unsupervised Matching of Identical Object Patterns and Its Applications
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Metadata
Title
Evaluating and Extending Trajectory Features for Activity Recognition
Authors
Ross Messing
Atousa Torabi
Aaron Courville
Chris Pal
Copyright Year
2013
Publisher
Springer London
Book
Advanced Topics in Computer Vision

Print ISBN: 978-1-4471-5519-5

Electronic ISBN: 978-1-4471-5520-1

Copyright Year: 2013

DOI
https://doi.org/10.1007/978-1-4471-5520-1_4

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