Citation:
Quinteros, D., Velastin, S.A. y Acuña, G. (2015). Characterisation of the spatial sensitivity of classifiers in pedestrian detection. 6th LatinAmerican Conference on Networked Electronic Media (LACNEM-2015).
xmlui.dri2xhtml.METS-1.0.item-contributor-funder:
European Commission Ministerio de Economía y Competitividad (España) Ministerio de Educación, Cultura y Deporte (España)
Sponsor:
The work described here was carried out as part of the OB-SERVE project funded by the Fondecyt Regular programme of Conicyt (Chilean Research Council for Science and Technology) under grant no. 1140209. Sergio A Velastin has re-ceived funding from the Universidad Carlos III de Madrid, the European Unions Seventh Framework Programme for research, technological development and demonstration under grant agreement no 600371, el Ministerio de Economa y Competitividad (COFUND2013-51509) el Ministerio de Educacin, cultura y Deporte (CEI-15-17) and Banco Santander.
Project:
Gobierno de España. COFUND2013-51509 info:eu-repo/grantAgreement/EC/PCOFUND-GA-2012-600371 Gobierno de España. CEI-15-17
In this paper, a study of the spatial sensitivity in the pedestrian detection context is carried out by a comparison of two descriptor-classifier combinations, using the well-known sliding window approach and looking for a well-tuned response of the detector. In this paper, a study of the spatial sensitivity in the pedestrian detection context is carried out by a comparison of two descriptor-classifier combinations, using the well-known sliding window approach and looking for a well-tuned response of the detector. By well-tuned, we mean that multiple detections are minimised so as to facilitate the usual non-maximal suppression stage. So, to guide the evaluation we introduce the concept of spatial sensitivity so that a pedestrian detection algorithm with good spatial sensitivity can reduce the number of classifications in the pedestrian neighbourhood, ideally to one. To characterise spacial sensitivity we propose and use a new metric to measure it. Finally we carry out a statistical analysis (ANOVA) to validate the results obtained from the metric usage.[+][-]
Description:
This paper has been presented at : 6th LatinAmerican Conference on Networked Electronic Media (LACNEM-2015)