Jan-Olof Eklundh

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Classifying materials from their appearance is a challenging problem, especially if illumination and pose conditions are permitted to change: highlights and shadows caused by 3D structure can radically alter a sample’s visual texture. Despite these difficulties, researchers have demonstrated impressive results on the CUReT database which contains many(More)
0262-8856/$ see front matter 2009 Elsevier B.V. A doi:10.1016/j.imavis.2009.05.005 * Corresponding author. Address: IDIAP Research In Marconi 19, Martigny, Switzerland. Tel.: +41 277 217 E-mail addresses: bcaputo@idiap.ch (B. Caputo), Hayman), fritz@mis.tu-darmstadt.de (M. Fritz), joe@n URLs: http://www.idiap.ch/bcaputo (B. Caputo), h darmstadt.de/mfritz(More)
The tracking and reconstruction of articulated human motion in 3D is a problem that has attracted a great deal of interest in the last years. A system that recovers 3D body pose from video sequences has applications in vision-based human-computer interaction , marker-less motion capture, animation, surveillance and entertainment such as computer games. The(More)
This paper describes techniques for fusing the output of multiple cues to robustly and accurately segment foreground objects from the background in image sequences. Two different methods for cue integration are presented and tested. The first is a probabilistic approach which at each pixel computes the likelihood of observations over all cues before(More)
We present an approach for deriving qualitative descriptions of contours containing structures at different (unknown) scales. The descriptions are in terms of straight a m , curved arcs with sign of curvature, corners, and points delimiting the arcs: inflexion points and transitions from straight to curved. Furthermore, the tangents at these points are(More)
When a visual observer moves forward the projections of the objects in the scene will move over the visual image. If an object extends vertically from the ground its image will move differently from the immediate background. This difference is called motion parallax [1,2]. Much work in automatic visual navigation and obstacle detection has been concerned(More)