Geometric hashing is a model-based recognition technique based on matching of transformation-invariant object representations stored in a hash table. In the last decade a number o...
Ehud Rivlin, Ilya Blayvas, Michael Lifshits, Micha...
Statistical methods, such as independent component analysis, have been successful in learning local low-level features from natural image data. Here we extend these methods for le...
Abstract. This paper presents a set of image operators for detecting regions in space-time where interesting events occur. To define such regions of interest, we compute a spatio-t...
In this paper, a new method is proposed to detect abnormal regions in colonoscopic images by patch-based classifier ensemble. Through supervised learning from image patches of var...
Kap Luk Chan, Peng Li, Shankar Muthu Krishnan, Yan...
Recent work has shown that effective methods for recognising objects or spatio-temporal events can be constructed based on receptive field responses summarised into histograms or ...
The reconstruction of objects from data in practical applications often leads to surfaces with small perturbations and other artifacts which make the detection of their ridges and...
Frederic F. Leymarie, Benjamin B. Kimia, Peter J. ...
This paper presents an adaptative algorithm for the segmentation of color images suited for document image analysis. The algorithm is based on a serialization of the k-means algor...
This paper describes a new approach in locating the segments of singing voice in pop musical songs. Initially, GLR distance measure is employed to temporally detect the boundaries...
We propose a novel energy minimisation framework for the dense reconstruction of stereo image sequences that incorporates data fidelity as well as spatial and temporal regularity....
Ben Appleton, Brian C. Lovell, Carlos Leung, Chang...