作者：
Oda, MAkamatsu, SFukamachi, HATR Human Information Processing Laboratories
Kyoto Japan 619-02 Shigeru Akamatsu received his B.E.
M.E. and Dr. of Eng. degrees in Mathematical Enginwring and Instrumentation Physics in 1975 1977 and 1994 respectively from the University of Tokyo Japan. In 1977 he joined the Electrical Communications Laboratories Nippon Telegraph and Telephone Public Corporation Yokosuka Japan. From 1977 through 1985 he was engaged in the research and development of optical character recognition systems for handwritten Chmese characters. During the academic year 1985-86 he was a Visiting Researcher at the University of California Irvine California U.S.A. Until 1992 he was a Senior Research Engineer Supervisor at W Human Interface Laboratories and conducted research on human image recognition with a special interest in face recognition. Since 1992 he has been with ATR Human Information Processing Research Laboratories Kyoto Japan where he is currently Head of Department 2. His research interests include computational and cognitive studies on high-level vision with a special interest in facial information processing by man and computer. He is a member of the Institute of Electronics Information and Communication Engineers of Japan the Information Processing Society of JapanACMand the IEEE Computer Society.Hidm Fukamachi received his B.E. degree in Image Technology from the Tokyo Institute of Polytechnics in 1990. He joined NTT Software Corp. in 1990
where he was engaged in the development of image processing software. Since 1993 he has been with ATR Human Information Processing Research Laboratories.
Some facial images are not necessarily clear images in the human brain. However, it can be easily judged whether a face matches the image in our mind;this is true even when the drawing or the expression of the target ...
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Some facial images are not necessarily clear images in the human brain. However, it can be easily judged whether a face matches the image in our mind;this is true even when the drawing or the expression of the target image is difficult to comprehend. This is because even if the image cannot be imagined like a picture, it does exist. The authors have proposed a system with which a retriever can retrieve an ambiguous target image from an image database. The system's retrieval efficiency and ease-of-retrieval were clarified by experiments using line drawn facial images. In this paper, the system is extended to photographs of faces. The most difficult problem in treating photographs is determining the retrieval key. One consideration is to add the subjective impressions or features of physical figures as keywords for each image data. Regardless of the method, however, significant manpower is necessary. The K-L expansion technique is used here, which has been verified as effective for face identification, and expect to need only a small amount of manpower. This paper investigates whether the technique can also be useful in ambiguous image retrieval.
The problem of egomotion recovery has been treated by using as input local image motion, with the published algorithms utilizing the geometric constraint relating 2-D local image motion (optical flow, correspondence, ...
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The problem of egomotion recovery has been treated by using as input local image motion, with the published algorithms utilizing the geometric constraint relating 2-D local image motion (optical flow, correspondence, ...
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The problem of egomotion recovery has been treated by using as input local image motion, with the published algorithms utilizing the geometric constraint relating 2-D local image motion (optical flow, correspondence, derivatives of the image flow) to 3-D motion and structure. Since it has proved very difficult to achieve accurate input (local image motion), a lot of effort has been devoted to the development of robust techniques. A new approach to the problem of egomotion estimation is taken, based on constraints of a global nature. It is proved that local normal flow measurements form global patterns in the image plane. The position of these patterns is related to the three dimensional motion parameters. By locating some of these patterns, which depend only on subsets of the motion parameters, through a simple search technique, the 3-D motion parameters can be found. The proposed algorithmic procedure is very robust, since it is not affected by small perturbations in the normal flow measurements. As a matter of fact, since only the sign of the normal flow measurement is employed, the direction of translation and the axis of rotation can be estimated with up to 100% error in the image measurements.< >
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