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A novel block-based bag of words (BBoW) method is proposed for robust face recognition. In our approach, a face image is partitioned into multiple blocks, dense SIFT features are then calculated and vector quantized into different codewords on each block respectively. Finally, histograms of codeword distribution on each local block are concatenated to represent the face image. Experimental results...
Face recognition is widely considered as one of the most promising biometric techniques, allowing high recognition rates without being too intrusive. Many approaches have been presented to solve this special pattern recognition problem, also addressing the challenging cases of face changes, mainly occurring in expression, illumination, or pose. On the other hand, less work can be found in literature...
Markerless, vision based estimation of human hand pose over time is a prerequisite for a number of robotics applications, such as learning by demonstration (LbD), health monitoring, teleoperation, human-robot interaction. It has special interest in humanoid platforms, where the number of degrees of freedom makes conventional programming challenging. Our primary application is LbD in natural environments...
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