We propose a novel approach to learn and recognize natural scene categories. Unlike previous work [9, 17], it does not require experts to annotate the training set. We represent t...
Fei-Fei Li 0002, Pietro Perona, California Institu...
In this paper, we present an efficient algorithm for 3D object recognition in presence of clutter and occlusions in noisy, sparse and unsegmented range data. The method uses a robu...
A real-world computer vision module must deal with a wide variety of environmental parameters. Object recognition, one of the major tasks of this vision module, typically requires...
We present a new adaptive algorithm for automatic detection of text from a natural scene. The initial cues of text regions are first detected from the captured image/video. An ada...
We present a semi-Markov model for recognizing scene text that integrates character and word segmentation with recognition. Using wavelet features, it requires only approximate lo...
Allen R. Hanson, Erik G. Learned-Miller, Jerod J. ...