No abstract

No abstract

In this paper, a new real-time and intelligent mobile robot system for path planning and navigation using stereo camera embedded on the pan/tilt system is proposed. In the proposed system, face area of a moving person is detected from a sequence of the stereo image pairs by using the YCbCr color model and using the disparity map obtained from the left and right images captured by the pan/tilt-controlled stereo camera system and depth information can be detected. And then, the distance between the mobile robot system and the face of the moving person can be calculated from the detected depth information. Accordingly, based-on the analysis of these data, three-dimensional objects can be detected.Finally, by using these detected data, 2-D spatial map for a visually guided robot that can plan paths, navigate surrounding objects and explore an indoor environment is constructed. From some experiments on target tracking with 480 frames of the sequential stereo images, it is analyzed that error ratio between the calculated and measured values of the relative position is found to be very low value of 1.4 % on average. Also, the proposed target tracking system has achieved a high speed of 0.04 sec/frame for target detection and 0.06 sec/frame for target tracking.

In this paper, a new stereoscopic image reconstruction technique using an adaptive disparity estimation algorithm is proposed and its performance is analyzed in terms of PSNR through comparison to that of the conventional disparity estimation algorithms. In the proposed method, the feature-based disparity estimation method in which Canny mask operator is used for detecting the edge information from the input stereo pair are used for extracting the feature value. And, the matching window size for reconstruction of stereoscopic image is adaptively selected depending on the magnitude of the feature value of the input stereo pair by comparing with the predetermined threshold value. That is, coarse matching is carried out in the region having a small feature value while dense matching is carried out in the region having a large feature value. This new approach can not only reduce mismatching possibility of the disparity vector mostly happened in the conventional dense disparity estimation with a small matching window size, but also reduce the blocking effect occurred in the disparity estimation with a large matching window size. From some experimental results, it is found that the proposed algorithm improves PSNR of the reconstructed image about 5.367.76 dB on the average than that of the conventional algorithms.

In this paper, a new real-time and intelligent face tracking system basing on the pan/tilt controlled stereo camera is proposed. In the proposed system moving human face is firstly detected from a sequence of the stereo image captured by the stereo camera system using a threshold value of YCbCr color model and its distance and area coordinates are measured and then, finally the stereo camera is controlled by using the pan/tilt system for tracking the moving face in real-time. Especially, color information of the face and geometric coordinate information of the stereo camera in which the pan/tilt system is embedded are used for extraction of 3D information of the human's face. From some experiments using a sequence of 1,280 frames of stereo input image, it is analyzed that the horizontal and vertical displacement on the center position of the face after tracking are kept to be very low values of 0.6% for 1,280 frames on average. Also, the error ratio between the measured and computed values is kept to be very low value of 0.5% on average in cartesian coordinates. This good experimental result finally suggests a possibility of implementing a new face tracking system having a high degree of accuracy and a very fast response time on the target by using the proposed algorithm.