3D-guided multiscale sliding window for pedestrian detection

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

Producción científica: Capítulo del libroContribución a congreso/conferenciarevisión exhaustiva

5 Citas (Scopus)

Resumen

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.

Idioma originalInglés
Título de la publicación alojadaPattern Recognition and Image Analysis - 7th Iberian Conference, IbPRIA 2015, Proceedings
EditoresJaime S. Cardoso, Roberto Paredes, Xosé M. Pardo
EditorialSpringer Verlag
Páginas560-568
Número de páginas9
ISBN (versión digital)9783319193892
DOI
EstadoPublicada - 2015
Publicado de forma externa
Evento7th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2015 - Santiago de Compostela, Espana
Duración: 17 jun 201519 jun 2015

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen9117
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia7th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2015
País/TerritorioEspana
CiudadSantiago de Compostela
Período17/06/1519/06/15

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