3D-guided multiscale sliding window for pedestrian detection

Alejandro González*, Gabriel Villalonga, German Ros, David Vázquez, Antonio M. López

*Corresponding author for this work

Research output: Book chapterConference contributionpeer-review

5 Citations (Scopus)

Abstract

The most relevant modules of a pedestrian detector are the candidate generation and the candidate classification. The former aims at presenting image windows to the latter so that they are classified as containing a pedestrian or not. Much attention has being paid to the classification module, while candidate generation has mainly relied on (multiscale) sliding window pyramid. However, candidate generation is critical for achieving real-time. In this paper we assume a context of autonomous driving based on stereo vision. Accordingly, we evaluate the effect of taking into account the 3D information (derived from the stereo) in order to prune the hundred of thousands windows per image generated by classical pyramidal sliding window. For our study we use a multimodal (RGB, disparity) and multi-descriptor (HOG, LBP, HOG+LBP) holistic ensemble based on linear SVM. Evaluation on data from the challenging KITTI benchmark suite shows the effectiveness of using 3D information to dramatically reduce the number of candidate windows, even improving the overall pedestrian detection accuracy.

Original languageEnglish
Title of host publicationPattern Recognition and Image Analysis - 7th Iberian Conference, IbPRIA 2015, Proceedings
EditorsJaime S. Cardoso, Roberto Paredes, Xosé M. Pardo
PublisherSpringer Verlag
Pages560-568
Number of pages9
ISBN (Electronic)9783319193892
DOIs
Publication statusPublished - 2015
Externally publishedYes
Event7th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2015 - Santiago de Compostela, Spain
Duration: 17 Jun 201519 Jun 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9117
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference7th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2015
Country/TerritorySpain
CitySantiago de Compostela
Period17/06/1519/06/15

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