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SIFT features have become extremely popular in computer vision because of their reliable matching qualities under changing lighting conditions. In Robotics they are ubiquitious in self localisation and mapping (SLAM), object tracking and recognition. However, the length of the descriptor is a major obstacle for real-time applications and mobile platforms where the computation time and storage capacity...
A face recognition system for simultaneous detection and pose estimation is presented. The algorithm proceeds in two steps: At first, separate face components such as eyes, nose and mouth are detected. This is done by a classification of modified SIFT features that are more robust to spatial displacements. Secondly, face-like part constellations are detected by an SVM based voting scheme. Inhibitive...
This article presents a SIFT-based object recognition method that avoids the typical problems of time-consuming code-book generation and curse of dimensionality in feature comparison. The first problem is solved by using an alphabet of completely synthetic feature vectors. The second problem is solved by using the Hamming-distance on binarised SIFT-features. The method is supported by competitive...
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