Analysis of Detection and Track on Partially Occluded Face

As a new field of information technology, biometrics recognition consists of the recognition of face, iris, retina, pronunciation etc. In recent years, Static face detection algorithms concerning the categories of detection technology have been raised, but these algorithms put their focus on the detection of clear face. The research of detection on partially occluded face has not yet been conducted. Under this circumstance, the thesis gives a brand new static detection and dynamic track algorithm on partially occluded face. This new algorithm is that the static partial face is detected by the YCbCr, the dynamic image sequences use a logic "and" operation to track the partial face, and then the static partial face and dynamic face are fitted, if the fitting value is smaller than the pre-value, the static partial face is considered as a non-face; otherwise the partial is a face. By analyzing the 50 graphs including 160 faces (60 partial faces and 100 clear faces), it has been found that the detection accuracy of the partial faces is 62% and the clear faces detection accuracy is 98%. This new algorithm can provide important reference to partial face detection. The algorithm still needs to be verified and improved further.