• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.89-101
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• 2015

This paper proposes a statistical model of 3-D positions when tracking moving targets using the uncooled infrared (IR) stereo camera system. The proposed model is derived from two errors. One is the position error which is caused by the sampling pixels in the digital image. The other is the timing jitter which results from the irregular capture-timing in the infrared cameras. The capture-timing in the IR camera is measured using the jitter meter designed in this paper, and the observed jitters are statistically modeled as Gaussian distribution. This paper derives an integrated probability distribution by combining jitter error with pixel position error. The combined error is modeled as the convolution of two error distributions. To verify the proposed statistical position error model, this paper has some experiments in tracking moving objects with IR stereo camera. The 3-D positions of object are accurately measured by the trajectory scanner, and 3-D positions are also estimated by stereo matching from IR stereo camera system. According to the experiments, the positions of moving object are estimated within the statistically reliable range which is derived by convolution of two probability models of pixel position error and timing jitter respectively. It is expected that the proposed statistical model can be applied to estimate the uncertain 3-D positions of moving objects in the diverse fields.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.1
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• pp.78-87
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• 1989

In this paper, a spatio-temporal gradient (STG) method with generalized least square estimation (GLSE) is proposed for the detection of an object motion in an image sequence corrupted by white Gaussian noise. The proposed method is applied to an automatic target tracker using a high speed 16-bit microprocessor in order to track one moving target in real time. Experimental results show that the proposed method has much better performance over the conventional one with least square estimation (LSE).

• Journal of Broadcast Engineering
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• v.19 no.3
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• pp.329-341
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• 2014

Kernel-based mean-shift object tracking has gained more interests nowadays, with the aid of its feasibility of reliable real-time implementation of object tracking. This algorithm calculates the best mean-shift vector based on the color histogram similarity between target model and target candidate models, where the color histograms are usually produced after uniform color-space quantization for the implementation of real-time tracker. However, when the image of target model has a reduced contrast, such uniform quantization produces the histogram model having large values only for a few histogram bins, resulting in a reduced accuracy of similarity comparison. To solve this problem, a non-uniform quantization algorithm has been proposed, but it is hard to apply to real-time tracking applications due to its high complexity. Therefore, this paper proposes a fast non-uniform color-space quantization method using the histogram equalization, providing an adjusted histogram distribution such that the bins of target model histogram have as many meaningful values as possible. Using the proposed method, the number of bins involved in similarity comparison has been increased, resulting in an enhanced accuracy of the proposed mean-shift tracker. Simulations with various test videos demonstrate the proposed algorithm provides similar or better tracking results to the previous non-uniform quantization scheme with significantly reduced computation complexity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.1027-1030
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• 2013

For the detection of objects in the videos, there are various ways that use the frequency transformation. In the videos, the images of objects could be changed slightly. Object detection methods using frequency transformation such as ASEF and MOSSE have the ability to renew the detection filter in order to deal with the change of object images. But these approaches are likely to fail the detection because the image changes often occur when they come out again after being hidden by other objects. What is worse, when they show up again, they appear in another place, not the original one. In this paper, a new proposal is present so that the detection can be carried out efficiently even when the images come out in other place, and the failure of the detection can be reduced.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2711-2713
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• 2000

능동시각시스템의 가장 큰 장점은 주어진 환경에 대해 능동적으로 반응할 수 있는 자유도가 있어 이를 활용하여 필요한 정보를 쉽게 추출할 수 있다는 점이다. 이를 위해서는 능동시각시스템의 시선을 원하는 위치로 이동시키는 것이 필요한데, 시스템의 여자유도 인해 해가 무수히 많이 존재하게 된다. 본 논문에서는 이러한 여자유도 문제를 기구의 동역학적 특성을 제한 조건으로 하여 최적의 해를 구하고 이를 이용해 각 관절을 제어하는 제어기를 설계하는 방법에 대해 소개한다. 설계된 제어기는 제작과 실험을 통해 고속으로 움직이는 물체를 실시간으로 추적하는 성능을 보였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.3C
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• pp.255-261
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• 2008

Conventional look-up table(LT) has gained a lot of speed increase in generation of digital holograms for 3D objects, but it has required an enormous memory size of the LT. In this paper, a novel approach to dramatically reduce the size of the conventional LT, still keeping its advantage of fast computational speed is proposed, which is called here a N-LT(novel look-up table) method. In the proposed method, only the fringe patterns of the center points on each image plane are pre-calculated, called elemental fringe patterns and stored in the look-up table. Then, the fringe patterns for other object points on each image plane can be obtained by simply shifting this pre-calculated elemental fringe pattern according to the displaced values from the center to those points and adding them together. Some experimental results revealed that the computational speed and the required memory size of the proposed approach are found to be 48.7 times faster than that of the ray-tracing method and 217 times smaller than that of the conventional LT method, respectively.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.38-48
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• 1996

We implemented and evaluated the preformance of a task level pipelined multicomputer "RV860-PIPE(Realtime Vision i860 system using PIPEline)" for computer vision applications. RV860-PIPE is a message-passing MIMD computer having ring interconnection network which is appropriate for vision processing. We designed the node computer of RV860-PIPE using a 64-bit microprocessor to have generality and high processing power for various vision algorithms. Furthermore, to reduce the communication overhead between node computers and between node computer and a frame grabber, we designed dedicated high speed communication channels between them. We showed the practical applicability of the implemented system by evaluting performances of various computer vision applications like edge detection, real-time moving object tracking, and real-time face recognition.