Head detection in stereo data for people counting and segmentation

B. Kröse, Tim van Oosterhout, S.C.J. Bakkes

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademic

35 Citations (Scopus)
59 Downloads (Pure)

Abstract

In this paper we propose a head detection method using range data from a stereo camera. The method is based on a technique that has been introduced in the domain of voxel data. For application in stereo cameras, the technique is extended (1) to be applicable to stereo data, and (2) to be robust with regard to noise and variation in environmental settings. The method consists of foreground selection, head detection, and blob separation, and, to improve results in case of misdetections, incorporates a means for people tracking. It is tested in experiments with actual stereo data, gathered from three distinct real-life scenarios. Experimental results show that the proposed method performs well in terms of both precision and recall. In addition, the method was shown to perform well in highly crowded situations. From our results, we may conclude that the proposed method provides a strong basis for head detection in applications that utilise stereo cameras.
Original languageEnglish
Title of host publicationVISAPP 2011
Place of PublicationAmsterdam
PublisherHogeschool van Amsterdam
Publication statusPublished - 2011

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