Adaptive algorithm selection, with applications in pedestrian detection

Shu Zhang, Qi Zhu, Amit Roy-Chowdhury

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Computer vision algorithms are known to be extremely sensitive to the environmental conditions in which the data is captured, e.g., lighting conditions and target density. Tuning of parameters or choosing a completely new algorithm is often needed to achieve a certain performance level. In this paper, we focus on this problem and propose a framework to automatically choose the 'best' algorithm-parameter combination (often referred to as the best algorithm for simplicity in this paper) for a certain input data. This necessitates developing a mechanism to switch among different algorithms and parameters as the nature of the input video changes. Specifically, our proposed algorithm calculates a similarity function between a test video segment and a training video segment. Similarity between training and test dataset indicates the same algorithm can be applied to both of them. We design a cost function with this similarity measure and a constraint on the number of switches. In the experiments, we apply our algorithm to the problem of pedestrian detection. We show how to adaptively select among 7 algorithm-parameter combinations and provide promising results on 3 publicly available datasets.

Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
PublisherIEEE Computer Society
Pages3768-3772
Number of pages5
Volume2016-August
ISBN (Electronic)9781467399616
DOIs
StatePublished - Aug 3 2016
Event23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States
Duration: Sep 25 2016Sep 28 2016

Other

Other23rd IEEE International Conference on Image Processing, ICIP 2016
CountryUnited States
CityPhoenix
Period9/25/169/28/16

Keywords

  • Adaptation
  • Algorithm selection
  • Pedestrian detection

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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  • Cite this

    Zhang, S., Zhu, Q., & Roy-Chowdhury, A. (2016). Adaptive algorithm selection, with applications in pedestrian detection. In 2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings (Vol. 2016-August, pp. 3768-3772). [7533064] IEEE Computer Society. https://doi.org/10.1109/ICIP.2016.7533064