An optimum filter for extracting a time-varying harmonic signal from the noise-corrupted measurement is proposed. It is derived as a solution of the least mean square estimation with consideration of the pitch estimation error even without any assumption on the filter model. We obtain a comb-like impulse response which consists of homologous and dilated distribution of weights just located periodically with a pitch interval. This remarkable structure is well suited to the proportionally expanding error of pitch repetition times. Examples of the filter design are presented, and the performance of noise suppression is examined by comparison with conventional comb filters.

This paper describes a new algorithm for finding the contours of a moving object in an image sequence. A distinctive feature of this algorithm is its complete bottom-up strategy from image data to a consistent contour description. In our algorithm, an input image sequence is immediately converted to a complete set of quasi logical spatio-temporal measures on each pixel, which provide constraints on varying brightness. Then, candidate regions in which to localize the contour are bounded based on consistent grouping among neighboring measures. This reduces drastically the ambiguity of contour location. Finally, Some mid-level constraints on spatial and temporal smoothness of moving boundaries are invoked, and they are combined with these low-level measures in the candidate regions. This is performed efficiently by the regularization over the restricted trajectory of the moving boundary in the candidate regions. Since any quantity is dimensionless, the results are not affected by varying conditions of camera and objects. We examine the efficiency of this algorithm through several experiments on real NTSC motion pictures with dynamic background and natulal textures.

This paper describes our newly developed intelligent sensor system which comprises two eyes and four ears on a movable head. It can acquire its dynamical visual and auditory image of its surrouding 3-D environment while showing humanlike behavior naturally and autonomously. The most important feature of the sensor system is in an autonomous and optimum sensory architecture of it. This enables the sensor to achieve 1) repid (5 ms) and accurate (2 deg) auditory localization, 2) rapid (0.5 s/65536 pixel) extraction of visual motion in marginal view, 3) rapid (several TV frames' time) eye movement and binocular fixation to a suddenly appeared object, 3) rapid (0.1 s/4096 pixel) extraction of 3-D object profile and image features, which is activated by its own auditory localization and motion detection. We describe in this paper the several key items for realizing this sensor.