• The KIPS Transactions:PartB
• /
• v.12B no.4 s.100
• /
• pp.429-436
• /
• 2005

A simple stereo matching algorithm using population-based incremental learning(PBIL) is proposed in this paper to decrease the general problem of genetic algorithms, such as memory consumption and inefficiency of search. PBIL is a variation of genetic algorithms using stochastic search and competitive teaming based on a probability vector. The structure of PBIL is simpler than that of other genetic algorithm families, such as serial and parallel ones, due to the use of a probability vector. The PBIL strategy is simplified and adapted for stereo matching circumstances. Thus, gene pool, chromosome crossover, and gene mutation we removed, while the evolution rule, that fitter chromosomes should have higher survival probabilities, is preserved. As a result, memory space is decreased, matching rules are simplified and computation cost is reduced. In addition, a scheme controlling the distance of neighbors for disparity smoothness is inserted to obtain a wide-area consistency of disparities, like a result of coarse-to-fine matchers. Because of this scheme, the proposed algorithm can produce a stable disparity map with a small fixed-size window. Finally, an alterative version of the proposed algorithm without using probability vector is also presented for simpler set-ups.

• Smart Media Journal
• /
• v.2 no.4
• /
• pp.60-65
• /
• 2013

In this paper, we propose a high-resolution disparity map generation method using a low-resolution time-of-flight (TOF) depth camera and color camera. The TOF depth camera is efficient since it measures the range information of objects using the infra-red (IR) signal in real-time. It also quantizes the range information and provides the depth image. However, there are some problems of the TOF depth camera, such as noise and lens distortion. Moreover, the output resolution of the TOF depth camera is too small for 3D applications. Therefore, it is essential to not only reduce the noise and distortion but also enlarge the output resolution of the TOF depth image. Our proposed method generates a depth map for a color image using the TOF camera and the color camera simultaneously. We warp the depth value at each pixel to the color image position. The color image is segmented using the mean-shift segmentation method. We define a cost function that consists of color values and segmented color values. We apply a weighted average filter whose weighting factor is defined by the random walk probability using the defined cost function of the block. Experimental results show that the proposed method generates the depth map efficiently and we can reconstruct good virtual view images.

• Journal of Broadcast Engineering
• /
• v.17 no.2
• /
• pp.363-373
• /
• 2012

This paper proposes a method to generate a depth image at an arbitrary intermediate view-point, which is targeting a video service for free-view, auto-stereoscopy, holography, etc. It assumes that the leftmost and the rightmost depth images are given and they both have been camera-calibrated and image-rectified. This method calculates and uses a disparity increment per depth value. In this paper, it is obtained by stereo matching for the given two depth image by considering more general cases. The disparity increment is used to find the location in the intermediate view-point depth image (IVPD) for each depth in the given images. Thus, this paper finds two IVPDs, from left image and from right image. Noises are removed and holes are filled in each IVPDs and the two results are combined to get the final IVPD. The proposed method was implemented and applied to several test sequences. The results revealed that the quality of the generated IVPD corresponds to 33.84dB of PSNR in average and it takes about 1 second to generate a HD IVPD. We evaluate that this image quality is quite good by considering the low correspondency among the left images, intermediate images, and the right images in the test sequences. If the execution speed is improved, the proposed method can be a very useful method to generate an IVPD at an arbitrary view-point, we believe.

• Journal of the Korea Society of Computer and Information
• /
• v.19 no.7
• /
• pp.17-25
• /
• 2014

In the devices that leave video records, it is an important issue to distinguish whether the input image is a real object or a photo when securing an identifying image. Using a single image and sensor, which is a simple way to distinguish the target from distance measurement has many weaknesses. Thus, this paper proposes a way to distinguish a simple photo and a real object by using stereo images. It is not only measures the distance to the target, but also checks a three-dimensional effect by making the depth map of the face area. They take pictures of the photos and the real faces, and the measured value of the depth map is applied to the learning algorithm. Exactly through iterative learning to distinguish between the real faces and the photos looked for patterns. The usefulness of the proposed algorithm was verified experimentally.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.54 no.4
• /
• pp.115-121
• /
• 2017

In this paper, the intelligent vision system for an effective and intelligent path-planning of an industrial AGV system based on stereo camera system is proposed. The depth information and disparity map are detected in the inputting images of a parallel stereo camera. The distance between the industrial AGV system and the obstacle detected and the 2D path coordinates obtained from the location coordinates, and then the relative distance between the obstacle and the other objects obtained from them. The industrial AGV system move automatically by effective and intelligent path-planning using the obtained 2D path coordinates. From some experiments on AGV system driving with the stereo images, it is analyzed that error ratio between the calculated and measured values of the distance between the objects is found to be very low value of 2% on average, respectably.

• The KIPS Transactions:PartB
• /
• v.17B no.1
• /
• pp.55-62
• /
• 2010

Human visual attention system has a remarkable ability to interpret complex scenes with the ease and simplicity by selecting or focusing on a small region of visual field without scanning the whole images. In this paper, a novel feature map generation and integration method for attention based visual information processing system is proposed. The depth information obtained from a stereo pair of images is exploited as one of spatial visual features to form a set of topographic feature maps in our approach. Comparative experiments show that correct detection rate of visual attention regions improves by utilizing depth feature compared to the case of not using depth feature.

• International Journal of Automotive Technology
• /
• v.7 no.3
• /
• pp.361-367
• /
• 2006

This paper describes a novel stereo vision based localization of free parking site, which recognizes the target position of automatic parking system. Pixel structure classification and feature based stereo matching extract the 3D information of parking site in real time. The pixel structure represents intensity configuration around a pixel and the feature based stereo matching uses step-by-step investigation strategy to reduce computational load. This paper considers only parking site divided by marking, which is generally drawn according to relevant standards. Parking site marking is separated by plane surface constraint and is transformed into bird's eye view, on which template matching is performed to determine the location of parking site. Obstacle depth map, which is generated from the disparity of adjacent vehicles, can be used as the guideline of template matching by limiting search range and orientation. Proposed method using both the obstacle depth map and the bird's eye view of parking site marking increases operation speed and robustness to visual noise by effectively limiting search range.

• The Transactions of the Korean Institute of Electrical Engineers D
• /
• v.49 no.12
• /
• pp.651-658
• /
• 2000

This paper presents a new method to extract traffic information such as number of passing vehicles and average speed by a pair of stereo road images. The whole process consists of the extraction of vehicles and the tracking of the extracted vehicles. For the extraction of vehicles, the outline of each vehicle is obtained by using binary region growing technique applied to disparity map based on multi-resolution stereo matching. The Kalman filter tracking algorithm is applied to the extracted vehicle outlines to determine the flow of vehicles. Experimental results show that the proposed method significantly improved recognition rate of vehicles over the conventional methods-frame difference and background elimination methods.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2017.06a
• /
• pp.117-120
• /
• 2017

본 논문은 스테레오 영상을 이용하여 3 차원 영상을 제공하기 위한 과정에서 중요한 변위 지도 생성 과정의 개선을 목적으로 한다. 변위 지도란, 서로 다른 시점의 두 영상 내에 매칭되는 대응점을 찾고 이와 같은 대응점들 간의 차를 통해 상대적 거리정보를 얻은 후, 이를 정규화하여 픽셀 값으로 나타낸 지도이다. 이에 본 논문에서는 변위 지도 생성 시, 물체들 간 대응점 매칭율을 높이기 위해 물체들의 외곽을 보존하여 형태를 뚜렷하게 하는 전처리 과정을 제안한다. 제안하는 방안은 제한 적응 히스토그램 평활화를 통해 물체들의 세부적인 특징들을 부각시키고, 양방향 필터를 통해 외각을 뚜렷하게 하는 전처리 과정을 포함한다. 본 논문에서는 제한 적응 히스토그램 평활화와 양방향 필터의 처리 과정을 분석하고, 실험결과를 통해 제안하는 전처리 과정을 검증하였다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2010.07a
• /
• pp.188-191
• /
• 2010

스테레오 매칭은 Robot Vision 분야에서 가장 활발하게 연구가 진행되어온 주제이다. 과거 많은 연구들은 스테레오 매칭 알고리즘의 정확도를 높이거나 처리속도를 개선하는 것 중 어느 한 쪽에만 집중하고 있었으며, 두 가지를 동시에 고려한 연구는 상대적으로 연구가 미흡한 실정이다. 본 논문에서는 영상의 공간적 중복 성질을 이용하여 스테레오 매칭 알고리즘의 처리속도를 획기적으로 개선하는 방법을 제안하고, 처리 속도 감소에 따라 증가되는 disparity map 추정 오차를 보상하는 기술을 제안한다. 구체적으로 Dynamic Programming (DP) 기반 스테레오 매칭 알고리즘에 제안한 속도 개선 방법을 적용하고, 개선된 Adaptive Support Weight Filter를 사용하여 보다 효과적인 오차 보상을 실현 하였다. 체계적인 실험을 통해, 본 논문에서 제안 하는 스테레오 매칭 알고리즘은 처리속도와 정확도를 동시에 개선할 수 있음을 검증하였다.