Publication: Characterisation of the spatial sensitivity of classifiers in pedestrian detection
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2015-09
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Tutors
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IEEE
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Abstract
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)
Keywords
Pedestrian detection, Spatial sensitivity, NMS, HOG, Classifier
Bibliographic 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).