• IEIE Transactions on Smart Processing and Computing
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• v.1 no.3
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• pp.161-170
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• 2012

This paper presents an efficient and robust approach for determining the correspondence between unbalanced stereo images. The disparity vectors were used instead of feature points, such as corners, to calculate a correspondence relationship. For a faster and optimal estimation, the vectors were classified into several regions, and the homography of each region was calculated using the RANSAC algorithm. The correspondence image was calculated from the images transformed by each homography. Although it provided good results under normal conditions, it was difficult to obtain reliable results in an unbalanced stereo pair. Therefore, a balancing method is also proposed to minimize the unbalance effects using the histogram specification and structural similarity index. The experimental results showed that the proposed approach outperformed the baseline algorithms with respect to the speed and peak-signal-to-noise ratio. This work can be applied to practical fields including 3D depth map acquisition, fast stereo coding, 2D-to-3D conversion, etc.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.7A
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• pp.520-528
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• 2003

This paper proposes a method of implementing synthetic stereo and an acoustic echo cancellation algorithm for multiple participant conference system. Synthetic stereo is generated by HRTF and two loudspeakers. A robust adaptive algorithm for synthetic stereo echo cancellation is proposed to reduce the weight misalignment due to near-end speech signals and ambient noises. The proposed adaptive algorithm is modified version of SMAP algorithm and the coefficients of adaptive filter is updated with cross correlation of input and estimation error signal normalized with sum of the autocorrelation of input signal and the power of the estimation error signal multiplied with projection order. This is more robust to projection order and ambient noise than conventional SMAP. Computer simulation show that the proposed algorithm effectively attenuates synthetic stereo acoustic echo.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.359-362
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• 2016

Face is an information unique to each person such as Iris, fingerprints, etc,. Research on face recognition are in progress continuously from the past to the present. Through these research, various face recognition methods have appeared. Among these methods, there are face recognition algorithms using the face data composed in stereo. In this paper, Convolutional Neural Network with Stereo Images as input was used for face recognition. This method showed better performance than the result of stereo face recognition using PCA that is used frequently in face recognition.

• Journal of Information Display
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• v.6 no.4
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• pp.16-25
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• 2005

In this paper, a new 3D object tracking system using the disparity motion vector (DMV) is presented. In the proposed method, the time-sequential disparity maps are extracted from the sequence of the stereo input image pairs and these disparity maps are used to sequentially estimate the DMV defined as a disparity difference between two consecutive disparity maps Similarly to motion vectors in the conventional video signals, the DMV provides us with motion information of a moving target by showing a relatively large change in the disparity values in the target areas. Accordingly, this DMV helps detect the target area and its location coordinates. Based on these location data of a moving target, the pan/tilt embedded in the stereo camera system can be controlled and consequently achieve real-time stereo tracking of a moving target. From the results of experiments with 9 frames of the stereo image pairs having 256x256 pixels, it is shown that the proposed DMV-based stereo object tracking system can track the moving target with a relatively low error ratio of about 3.05 % on average.

• Proceedings of the KSRS Conference
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• v.2
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• pp.772-775
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• 2006

Muilti-dimensional feature vector matching algorithm uses multiple features such as intensity, gradient, variance, first or second derivative of a pixel to find correspondence pixels in stereo images. In this paper, we proposed a new method for adjusting automatically the weight of feature in multi-dimensional feature vector matching considering sharpeness of a pixel in feature vector distance curve. The sharpeness consists of minimum and maximum vector distances of a small window mask. In the experiment we used IKONOS satellite stereo imagery and obtained accurate matching results comparable to the manual weight-adjusting method.

• Proceedings of the Optical Society of Korea Conference
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• 2007.02a
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• pp.125-126
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• 2007

This paper discussed a method for estimating the distance using the stereo zoom lens module. A method for estimating the distance using single zoom lens is limited in convergence angle. So, we composed horizontal moving camera and estimated the distance. In the experiment, we get the wider convergence angle and more precise distance than single camera's.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.49 no.3
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• pp.53-61
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• 2012

This paper proposes a real-time distance measurement system of high temperature and high speed target using infrared stereo camera. We construct an infrared stereo camera system that measure the difference between target and background temperatures for automatic target measurement. First, the proposed method detects target region based on target motion and intensity variation of local region using difference between target and background temperatures. Second, stereo matching by left and right target information is used to estimate disparity about real-time distance of target. In the proposed method using infrared stereo camera system, we compare distances in three dimension trajectory measuring instrument and in infrared stereo camera measurement. In this experiment from three video data, the result shows an average 9.68% distance error rate. The proposed method is suitable for distance and position measurement of varied targets using infrared stereo system.

• Journal of Internet Computing and Services
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• v.11 no.6
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• pp.21-29
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• 2010

In this paper, we propose the system which detects the speaker, who is speaking currently, among a number of users. A proposed speaker detection system based on stereo vision and audio is mainly composed of the followings: a position estimation of speaker candidates using stereo camara and microphone, a current speaker detection, and a speaker information acquisition based on a mobile device. We use the haar-like features and the adaboost algorithm to detect the faces of speaker candidates with stereo camera, and the position of speaker candidates is estimated by a triangulation method. Next, the Time Delay Of Arrival (TDOA) is estimated by the Cross Power Spectrum Phase (CPSP) analysis to find the direction of source with two microphone. Finally we acquire the information of the speaker including his position, voice, and face by comparing the information of the stereo camera with that of two microphone. Furthermore, the proposed system includes a TCP client/server connection method for mobile service.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.10 no.2
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• pp.25-30
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• 1992

Most algorithms in computer vision and digital photogrammetry assume that digital stereo pairs are registered in epipolar geometry. But, an aerial stereo pair is not likely to be in epiplar geometry since the attitude of the camera at the instant of exposure is different at every exposure station. In this paper, stereo digital imagery is obtained from aerial stereo pair by scanner. Then procesure to resample the digital imagery to epipolar geometry using exterior orientation elements after absolute orientation is described. As a result, a stereo imagery in epipolar geometry is produced from stereo digital imagery. Epipolar imagery in this paper is applied to the image matching method by digital image correlation technique. Then, a digital elevation model is produced from the result of image matching. The digital elevation model in this paper is compared to the other digital elevation model produced by analytical plotter. As a result, an economical method to generate digital elevation model is presented.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.2
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• pp.198-204
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• 2012

Tracking and recognition of robots are required for the cooperation task of robots in various environments. In the paper, a tracking control system of moving robot using stereo image processing, code-book model and fuzzy controller is proposed. First, foreground and background images are separated by using code-book model method. A candidate region is selected based on the color information in the separated foreground image and real distance of the robot is estimated from matching process of depth image that is acquired through stereo image processing. The open and close processing of image are applied and labeling according to the size of mobile robot is used to recognize the moving robot effectively. A fuzzy tracking controller using distance information and mobile information by stereo image processing is designed for effective tracking according to the movement velocity of the target robot. The proposed fuzzy tracking control method is verified through tracking experiments of mobile robots with stereo camera.