In this paper, we address the problem of representing human actions using visual cues for the purpose of learning and recognition. Traditional approaches model actions as space-ti...
Visual recognition of human actions in video clips has been an active field of research in recent years. However, most published methods either analyse an entire video and assign ...
We present a mobile vision system for multi-person tracking in busy environments. Specifically, the system integrates continuous visual odometry computation with tracking-bydetect...
Andreas Ess, Bastian Leibe, Konrad Schindler, Luc ...
We present a new 3D scanning method using modulated phase-shifting. Optical scanning of complex objects or scenes with significant global light transport, such as subsurface scatt...
Tongbo Chen, Hans-Peter Seidel, Hendrik P. A. Lens...
In this paper, we propose a new approach for face shape recovery from a single image. A single near infrared (NIR) image is used as the input, and a mapping from the NIR tensor sp...
Lambert's model is widely used in low level computer vision algorithms such as matching, tracking or optical flow computation for example. However, it is well known that thes...
The popular bag-of-features representation for object recognition collects signatures of local image patches and discards spatial information. Some have recently attempted to at l...
We propose a novel step toward the unsupervised segmentation of whole objects by combining "hints" of partial scene segmentation offered by multiple soft, binary mattes....
Andrew N. Stein, Thomas S. Stepleton, Martial Hebe...
Because of the large variation across different environments, a generic classifier trained on extensive data-sets may perform sub-optimally in a particular test environment. In th...