Paper
8 February 2017 An improved TLD with Harris corner and color moment
Author Affiliations +
Proceedings Volume 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016); 102251P (2017) https://doi.org/10.1117/12.2267682
Event: Eighth International Conference on Graphic and Image Processing, 2016, Tokyo, Japan
Abstract
Video tracking is a main field of computer vision, and TLD algorithm plays a key role in long-term tracking. However, the original TLD ignores the color features of patch in detection, and tracks the common points from grid, then, the tracking accuracy is limited to both of them. This paper presents a novel TLD algorithm with Harris corner and color moment to overcome this drawback. Instead of tracking common points, we screen more important points utilizing Harris corner to reject a half patches, these points are better able to show the object’s textural features. In addition, the color moment classifier replaces patch variance to reduce the errors of detection. The classifier compares mine-dimensional color moment vectors so that it can keep the TLD’s stable speed. Experiment has proved that our TLD tracks a more reliable position and higher ability without affecting the speed.
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ling Li, Kai Liu, Fei Cheng, and Di Bao "An improved TLD with Harris corner and color moment", Proc. SPIE 10225, Eighth International Conference on Graphic and Image Processing (ICGIP 2016), 102251P (8 February 2017); https://doi.org/10.1117/12.2267682
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Cited by 3 scholarly publications.
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KEYWORDS
Detection and tracking algorithms

Sensors

Video

Computer vision technology

Machine vision

Quantization

Binary data

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