Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

6-2013

Abstract

This paper presents a novel locality sensitive histogram algorithm for visual tracking. Unlike the conventional image histogram that counts the frequency of occurrences of each intensity value by adding ones to the corresponding bin, a locality sensitive histogram is computed at each pixel location and a floating-point value is added to the corresponding bin for each occurrence of an intensity value. The floating-point value declines exponentially with respect to the distance to the pixel location where the histogram is computed, thus every pixel is considered but those that are far away can be neglected due to the very small weights assigned. An efficient algorithm is proposed that enables the locality sensitive histograms to be computed in time linear in the image size and the number of bins. A robust tracking framework based on the locality sensitive histograms is proposed, which consists of two main components: a new feature for tracking that is robust to illumination changes and a novel multi-region tracking algorithm that runs in real time even with hundreds of regions. Extensive experiments demonstrate that the proposed tracking framework outperforms the state-of-the-art methods in challenging scenarios, especially when the illumination changes dramatically.

Keywords

Illumination changes; Illumination invariant; Image histograms; Intensity values; Locality sensitives; State-of-the-art methods; Tracking algorithm; Visual tracking

Discipline

Databases and Information Systems | Theory and Algorithms

Research Areas

Information Systems and Management

Publication

Proceedings of the 26th IEEE Conference on Computer Vision and Pattern Recognition, Portland, USA, 2013 Jun 23-28

First Page

2427

Last Page

2434

Identifier

10.1109/CVPR.2013.314

Publisher

IEEE

City or Country

New Jersey

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1109/CVPR.2013.314

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