Learning multi‐planar scene models in multi‐camera videos. Issue 1 (1st February 2015)

• Record Type: Journal Article
• Authors: Yin, Fei; Velastin, Sergio A.; Ellis, Tim; Makris, Dimitrios
• Is Part Of: IET computer vision. Volume 9:Issue 1(2015)
• Page Start: 25
• Page End: 40
• Publication Date: 2015-02-01
• Subjects: image sensors -- video signal processing -- image segmentation; learning multiplanar scene models -- multicamera videos -- man made environments -- geometry -- pedestrian heights -- camera field of view -- plane regions -- image pixel -- tracking algorithms; Computer vision -- Periodicals; Pattern recognition systems -- Periodicals; 006.37
• DOI: 10.1049/iet-cvi.2013.0261
• Languages: English
• ISSNs: 1751-9632

Abstract

Abstract : Many man‐made environments are constructed with multiple levels where people walk, joined by stairs, ramps and overpasses. This study proposes a novel method to learn the geometry of a scene containing more than a single ground plane by tracking pedestrians and combining information from multiple views. The method estimates a scene model with multiple planes by measuring the variation of pedestrian heights across each camera's field of view. It segments the image into separate plane regions, estimating the relative depth and altitude for each image pixel, thus building a three‐dimensional reconstruction of the scene. By estimating the multiple planes, the method enables tracking algorithms to follow objects (pedestrians and/or vehicles) that are moving on different ground planes in the scene. The authors also introduce what they believe is the first public dataset with pedestrian traffic on multiple planes to encourage other researchers to compare their work in this field.