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SIFT is one of the feature region extraction methods. It is widely used in various fields including object recognition, mosaic object tracking, etc. However, since SIFT requires lots of arithmetic operations, it is not appropriate for real-time use. Therefore, many researchers has been tried to prepare other measures. SIFT using PCA or SURF is one of them. This paper is to study about the real-time...
In this paper the real-time face region was detected by suggesting the rectangular feature-based classifier and the robust detection algorithm that satisfied the efficiency of computation and detection performance was suggested. By using the detected face region as a recognition input image, in this paper the face recognition method combined with PCA and the multi-layer network which is one of the...
This paper proposes a classifier based on rectangular feature to detect face in real time. The goal is to realize a strong detection algorithm which satisfies both efficiency in calculation and detection performance. The proposed algorithm consists of the following three stages: Feature creation, classifier study and real time facial domain detection. Feature creation organizes a feature set with...
Recently the importance of studies to recognize the shape of human hands in realtime is being more stressed to implement the user-friendly user interface. However, human hands have a large degree of freedom and thus it is very difficult to accurately recognize the hand shape, especially in a complicated background of the color same as the skin color. In this study, we detect the fingertip, without...
This paper describes 3-dimensional (3D) gesture recognition using principal component analysis. Existing 2-dimensional gesture recognition systems have shortcomings such as limitation of motion. In order to solve this problem, motion recognition systems using 3D information were proposed. As vision-based 3D information has a number of dimensions as well as a lot of errors, however, it was difficult...
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