Performance improvement of multi-class detection using greedy algorithm for Viola-Jones cascade selection

Alexander A. Tereshin; Sergey A. Usilin; Vladimir V. Arlazarov

doi:10.1117/12.2310101

13 April 2018 Performance improvement of multi-class detection using greedy algorithm for Viola-Jones cascade selection

Alexander A. Tereshin, Sergey A. Usilin, Vladimir V. Arlazarov

Proceedings Volume 10696, Tenth International Conference on Machine Vision (ICMV 2017); 106960D (2018) https://doi.org/10.1117/12.2310101
Event: Tenth International Conference on Machine Vision, 2017, Vienna, Austria

Abstract

This paper aims to study the problem of multi-class object detection in video stream with Viola-Jones cascades. An adaptive algorithm for selecting Viola-Jones cascade based on greedy choice strategy in solution of the N-armed bandit problem is proposed. The efficiency of the algorithm on the problem of detection and recognition of the bank card logos in the video stream is shown. The proposed algorithm can be effectively used in documents localization and identification, recognition of road scene elements, localization and tracking of the lengthy objects , and for solving other problems of rigid object detection in a heterogeneous data flows. The computational efficiency of the algorithm makes it possible to use it both on personal computers and on mobile devices based on processors with low power consumption.

Citation Download Citation

Alexander A. Tereshin, Sergey A. Usilin, and Vladimir V. Arlazarov "Performance improvement of multi-class detection using greedy algorithm for Viola-Jones cascade selection", Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 106960D (13 April 2018); https://doi.org/10.1117/12.2310101

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KEYWORDS

Video

Detection and tracking algorithms

Image quality

Video processing

Cameras

Roads

Computing systems

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