出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Face detection algorithms are used to detect the human in various industry fields. A typical facedetection algorithm such as Haar Feature-based Cascade Classifier gives us an easier way todetect human face. It consists of several classifiers which contain complicated arithmeticoperations. Several classifiers constitute the cascade which can detect each element of humanface. The more cascades are contained in the algorithm to detect elements of human face, themore it takes a time to detect human face. The previous cascade hardly recognize real human,since previous cascade processes only one source from image source. In this paper, we presenta new cascade method for human face detection which exploits several classifiers for data notonly from image source but also various heterogeneous sensors. Cascades consist of varioussensors based on tuple data type could be operated quickly. It provides more accuracy of realhuman face detection, reduces the number of classifier for high speed processing in real-time.
