Ken-ichi Hidai

Robust face detection against brightness fluctuation and size variation

Proposes a face detection method intended to be used for a practical intelligent environment and human-interactive robot. Face detection and recognition are very crucial for such applications. However in the real situation, it is not easy to realize the robust detecting function because position, size, and brightness of the face image are very changeable. The proposed method solves these problems by combining correlation-based pattern matching, histogram equalization, skin color extraction, and multiple scale images generation. The authors have implemented a prototype system based upon the proposed method and conducted some experiments using the system. Results support the effectiveness of the proposed idea.

Convergence analysis of online linear discriminant analysis

Convergence of a matrix dynamics for online LDA is analyzed. Especially, stable spurious solutions are pointed out and two schemes to prevent the spurious solutions are proposed. The performance of the algorithm is confirmed by simulations of face identification.

Successive learning of linear discriminant analysis: Sanger-type algorithm

Linear discriminant analysis (LDA) is applied to broad areas, e.g. image recognition. However, successive learning algorithms for LDA are not sufficiently studied while they have been well established for principal component analysis (PCA). A successive learning algorithm which does not need N/spl times/N matrices has been proposed for LDA (Hiraoka and Hamahira, 1999, and Hiraoka et al., 2000), where N is the dimension of data. In the present paper, an improvement of this algorithm is examined based on Sangers (1989) idea. By the original algorithm, we can obtain only the subspace which is spanned by major eigenvectors. On the other hand, we can obtain major eigenvectors themselves by the improved algorithm.

Implementing a Face Detection System Practically Robust against Size Variation and Brightness Fluctuation for Distributed Autonomous Human Supporting Robotic Environment

This paper presents a robust face detection system intended to be used for practical human interactive distributed robotic environment. Towards future aging society, there are much expectation and social demands for such human interactive environment that is possible to collaborate and support humans. Typical examples are Intelligent Room at MIT, Intelligent Space at University of Tokyo, Easy Living at Microsoft Research, and so forth. For these distributed robotic environment, face detecting function of the each agents are very crucial. However, in the real situation, it cannot be easy to realize the robust detection, because position, size, and brightness of face image are much changeable.

Robust face detection for human interactive mobile robot

This paper proposes a novel face detection method to be used for practical human interactive mobile robot. Towards future aging society, there are much expectation and social demand for a mobile robot that is possible to interactively collaborate and support human. Typical examples are pet robot and service robot. Guard robot is another example. Face detection and recognition are very crucial for such applications. However, in the real situation, it is not easy to realize the robust detecting function because position, size, and brightness of face image are much changeable. The proposed method solves these problems by combining correlation-based pattern matching, histogram equalization, skin color extraction, and multiple scale images generation. The authors have implemented a prototype system based upon the proposed method and conducted some experiments using the system. Experimental results support effectiveness of the proposed idea.

Virtual video tape: a novel development tool for real-time motion image understanding

This paper proposes Virtual Video Tape (VVT). It is a randomly accessible motion image recorder in main memory. VVT is realized with only software, not hardware. It is intended as a tool for real-time motion image understanding research. Recent remarkable progress of PC hardware enables to use gigabyte order main memory. By utilizing such large sized memory, there is a possiblity to realize motion image recorder with software. Thus we propose VVT as an example of this kind image recorder. Utilizing current components, recording time can be expected as minutes order. Since the proposed VVT is fully digital, there is no analog medium nor possibility for degradation of image quality. Since there is no deterioration of playback image and no rewinding, VVT must contribute to program development for motion image understanding. Based upon the proposed idea, the authors have implemented a prototype VVT and used the prototype to develop visual tracking, real-time face detection and so forth. Through the implementation and experience of the usage, we have confirmed feasibility and effectiveness of the proposed idea. In this paper, the authors discuss background, required functions and structure of the recorder. Some implementation issues are also described.

Concept and design philosophy of a person-accompanying robot

This paper proposes a person accompanying robot as a novel human collaborative robot. The person accompanying robot is such legged mobile robot that is possible to follow the person utilizing its vision. towards future aging society, human collaboration and human support are required as novel applications of robots. Such human collaborative robots share the same space with humans. But conventional robots are isolated from humans and lack the capability to observe humans. Study on human observing function of robot is crucial to realize novel robot such as service and pet robot. To collaborate and support humans properly human collaborative robot must have capability to observe and recognize humans. Study on human observing function of robot is crucial to realize novel robot such as service and pet robot. The authors are currently implementing a prototype of the proposed accompanying robot.As a base for the human observing function of the prototype robot, we have realized face tracking utilizing skin color extraction and correlation based tracking. We also develop a method for the robot to pick up human voice clearly and remotely by utilizing microphone arrays. Results of these preliminary study suggest feasibility of the proposed robot.