An introduction on distinguish tracking frameworks: methods and experiments

Haiyang Zhang

doi:10.1117/12.2622698

1 December 2021 An introduction on distinguish tracking frameworks: methods and experiments

Haiyang Zhang

Proceedings Volume 12079, Second IYSF Academic Symposium on Artificial Intelligence and Computer Engineering; 120791H (2021) https://doi.org/10.1117/12.2622698
Event: 2nd IYSF Academic Symposium on Artificial Intelligence and Computer Engineering, 2021, Xi'an, China

Abstract

Visual object tracking aims to capture the given target in the whole sequence, where the target will suffer challenges such as occlusion, motion blur, distractors, and scale variation. Several popular frameworks are proposed for improving accuracy and speed. This paper aims to review the existing tracking frameworks, such as correlation filter, Siamese network, and multi-domain network and their variants. We also give a brief comparison of the OTB benchmark. Our review can give an in-depth introduction to visual object tracking tasks and help beginners recognize this area efficiently.

Citation Download Citation

Haiyang Zhang "An introduction on distinguish tracking frameworks: methods and experiments", Proc. SPIE 12079, Second IYSF Academic Symposium on Artificial Intelligence and Computer Engineering, 120791H (1 December 2021); https://doi.org/10.1117/12.2622698

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KEYWORDS

Image filtering

Electronic filtering

Detection and tracking algorithms

Filtering (signal processing)

Optical tracking

Convolution

Feature extraction

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