We describe an ensemble approach to learning1 salient regions from data partitioned according to the2 distributed processing requirements of large-scale sim-3 ulations. The volume...
Larry Shoemaker, Robert E. Banfield, Larry O. Hall...
Hough transform based object detectors learn a mapping from the image domain to a Hough voting space. Within this space, object hypotheses are formed by local maxima. The votes con...
While great strides have been made in detecting and localizing specific objects in natural images, the bottom-up segmentation of unknown, generic objects remains a difficult chall...
In this paper, we propose a new object detection method that does not need a learning mechanism. Given a hand-drawn model as a query, we can detect and locate objects that are sim...
Chih-Wen Su, Mark Liao, Yu-Ming Liang, Hsiao-Rong ...
Appearance Models (AM) are commonly used to model appearance and shape variation of objects in images. In particular, they have proven useful to detection, tracking, and synthesis...
Fernando De la Torre, Alvaro Collet, Manuel Quero,...