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Spotting recognition of head gestures from color image series

Presents an approach for spotting recognition of human head gestures from color image series. First, we use an algorithm based on a perceptually uniform color system to detect skin color region and hair color region of the face from input images. Then, the 3D pose of the head relative to the camera is estimated by calculating the primary moment and secondary moment of the skin color region and the hair color region. The standard patterns of each gesture were represented by the sequence of rotation angles in X, Y, Z axis, and the head area. Moreover the human head gestures were recognized by using the continuous dynamic programming algorithm to compare input image series with the standard patterns. Extensive experiments show the effectiveness of this approach in the human head gestures recognition from live video sequences with different people even wearing glasses, with different head size, and with unknown complex background.