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Enhanced Aggregated Channel Features Detector for Pedestrian Detection Using Parameter Optimisation and Deep Features

Conference paper
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Part of the Communications in Computer and Information Science book series (CCIS, volume 841)

Abstract

Aggregated Channel Features (ACF) proposed by Dollar et al. provide strong framework for pedestrian detection. Many variants of ACF detector achieved state of the art result using deep features along with aggregated channel features. In this paper we propose a hybrid method for pedestrian detection using a parameter optimized variant of ACF detector with decorrelated channels as region proposer followed by a deep CNN for feature extraction. Our proposed method effectively handles the issues of false positives and detection of small instances of pedestrians. The proposed detector gives the best result among the different variants of the ACF detectors in Caltech dataset with the best localization and is second to the best performing detector available till date.

Keywords

Pedestrian detection ACF detector Boosting algorithm 

Notes

Acknowledgements

We gratefully acknowledge for the research fellowship (3501/(NET-DEC.2014)) provided by the University Grants Commission (UGC) Govt. of India.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.College of Engineering TrivandrumThiruvananthapuramIndia

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