Spatiotemporal stacked sequential learning for Pedestrian detection

Alejandro González, David Vázquez, Sebastian Ramos, Antonio M. López, Jaume Amores

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4 Citas (Scopus)


Pedestrian classifiers decide which image windows contain a pedestrian. In practice, such classifiers provide a relatively high response at neighbor windows overlapping a pedestrian, while the responses around potential false positives are expected to be lower. An analogous reasoning applies for image sequences. If there is a pedestrian located within a frame, the same pedestrian is expected to appear close to the same location in neighbor frames. Therefore, such a location has chances of receiving high classification scores during several frames, while false positives are expected to be more spurious. In this paper we propose to exploit such correlations for improving the accuracy of base pedestrian classifiers. In particular, we propose to use two-stage classifiers which not only rely on the image descriptors required by the base classifiers but also on the response of such base classifiers in a given spatiotemporal neighborhood. More specifically, we train pedestrian classifiers using a stacked sequential learning (SSL) paradigm. We use a new pedestrian dataset we have acquired from a car to evaluate our proposal at different frame rates. We also test on well known dataset, Caltech. The obtained results show that our SSL proposal boosts detection accuracy significantly with a minimal impact on the computational cost. Interestingly, SSL improves more the accuracy at the most dangerous situations, i.e. when a pedestrian is close to the camera.

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
Número de páginas10
ISBN (versión digital)9783319193892
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)
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349


Conferencia7th Iberian Conference on Pattern Recognition and Image Analysis, IbPRIA 2015
CiudadSantiago de Compostela


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