In recent years Kernel Principal Component Analysis (Kernel PCA) has gained much attention because of its ability to capture nonlinear image features, which are particularly impor...
We describe a method for training object detectors using a generalization of the cascade architecture, which results in a detection rate and speed comparable to that of the best p...
Abstract: We propose a novel probabilistic method for detection of objects in noisy images. The method uses results from percolation and random graph theories. We present an algori...
We present a shape-based algorithm for detecting and
recognizing non-rigid objects from natural images. The existing
literature in this domain often cannot model the objects
ver...
Xiang Bai, Xinggang Wang, Longin Jan Latecki, Weny...
We study visual attention by detecting a salient object in an input image. We formulate salient object detection as an image segmentation problem, where we separate the salient obj...
Tie Liu, Jian Sun, Nanning Zheng, Xiaoou Tang, Heu...