• Title/Summary/Keyword: Disparity Space

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Superpixel-based Vehicle Detection using Plane Normal Vector in Dispar ity Space

  • Seo, Jeonghyun;Sohn, Kwanghoon
    • Journal of Korea Multimedia Society
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    • v.19 no.6
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    • pp.1003-1013
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    • 2016
  • This paper proposes a framework of superpixel-based vehicle detection method using plane normal vector in disparity space. We utilize two common factors for detecting vehicles: Hypothesis Generation (HG) and Hypothesis Verification (HV). At the stage of HG, we set the regions of interest (ROI) by estimating the lane, and track them to reduce computational cost of the overall processes. The image is then divided into compact superpixels, each of which is viewed as a plane composed of the normal vector in disparity space. After that, the representative normal vector is computed at a superpixel-level, which alleviates the well-known problems of conventional color-based and depth-based approaches. Based on the assumption that the central-bottom of the input image is always on the navigable region, the road and obstacle candidates are simultaneously extracted by the plane normal vectors obtained from K-means algorithm. At the stage of HV, the separated obstacle candidates are verified by employing HOG and SVM as for a feature and classifying function, respectively. To achieve this, we trained SVM classifier by HOG features of KITTI training dataset. The experimental results demonstrate that the proposed vehicle detection system outperforms the conventional HOG-based methods qualitatively and quantitatively.

Income-related health inequalities across regions in Korea - a case of adolescents (우리나라 건강 불균등의 요인과 지역별 비교 - 청소년을 중심으로)

  • Ahn, Byung-Chul;Joung, Hyo-Jee
    • Journal of the Korean Society of School Health
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    • v.22 no.2
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    • pp.25-36
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    • 2009
  • Purpose: The purpose of this study was to estimate income-related health inequalities among adolescent population across regions in Korea. Methods: Data of 8,456 adolescents from 1998, 2001, 2005, 2007 Korean Health and Nutrition Examination Survey were used for the analysis. True health status was proxied by self-rated health and overweight status. Per capita income was computed from household monthly average income adjusted by consumer price with base year 2005. Adolescent health inequalities were estimated by Concentration Index (CI) across income and space. Results: Ill health score was related with age (p<0.0001), gender (p=0.0155) and income (p<0.0001). Negative relationship between income and ill-health indicated that higher income group tended to enjoy better health and less overweight. These evidences suggested ill health were accumulated on the economically disadvantaged adolescents. The size of health inequalities (ill-health score) were estimated as CI=-0.057 and CI=-0.030 across income groups and regions, respectively. Comparable measures of within region health disparities were also observed. Conclusion: Since health disparity among adolescent population was small compared to adult population, lessening adolescent health inequality could be a helpful way of mitigating health disparities in later stage. Considering life stage of adolescents, school system and local communities could play important roles toward adolescent health distribution. Although health disparity between regions existed, health disparity within a region should not be neglected.

Object Contour Tracking Using Snakes in Stereo Image Sequences (스테레오 동영상에서 스네이크를 이용한 객체윤곽 추적 알고리즘)

  • Kim Shin-Hyoung;Jang Jong Whag
    • The KIPS Transactions:PartB
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    • v.12B no.7 s.103
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    • pp.767-774
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    • 2005
  • In this paper, we present a snake-based scheme for tracking object contour using disparity information taken from a stereo image sequence with cluttered background. The proposed method is composed of two steps. First, 3-D motion of object is estimated and candidate snake points are selected in disparity space. Second, object contour is extracted by using a modified snake algorithm with disparity information. The proposed algorithm can successfully extract the concave contour of objects and track the object contour in complex image. Performance of the proposed algorithm has been verified by simulation.

SLAM Method by Disparity Change and Partial Segmentation of Scene Structure (시차변화(Disparity Change)와 장면의 부분 분할을 이용한 SLAM 방법)

  • Choi, Jaewoo;Lee, Chulhee;Eem, Changkyoung;Hong, Hyunki
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.8
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    • pp.132-139
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    • 2015
  • Visual SLAM(Simultaneous Localization And Mapping) has been used widely to estimate a mobile robot's location. Visual SLAM estimates relative motions with static visual features over image sequence. Because visual SLAM methods assume generally static features in the environment, we cannot obtain precise results in dynamic situation including many moving objects: cars and human beings. This paper presents a stereo vision based SLAM method in dynamic environment. First, we extract disparity map with stereo vision and compute optical flow. We then compute disparity change that is the estimated flow field between stereo views. After examining the disparity change value, we detect ROIs(Region Of Interest) in disparity space to determine dynamic scene objects. In indoor environment, many structural planes like walls may be determined as false dynamic elements. To solve this problem, we segment the scene into planar structure. More specifically, disparity values by the stereo vision are projected to X-Z plane and we employ Hough transform to determine planes. In final step, we remove ROIs nearby the walls and discriminate static scene elements in indoor environment. The experimental results show that the proposed method can obtain stable performance in dynamic environment.

Towards the Saturation Throughput Disparity of Flows in Directional CSMA/CA Networks: An Analytical Model

  • Fan, Jianrui;Zhao, Xinru;Wang, Wencan;Cai, Shengsuo;Zhang, Lijuan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.4
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    • pp.1293-1316
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    • 2021
  • Using directional antennas in wireless Ad hoc networks has many superiorities, including reducing interference, extending transmission range, and increasing space division multiplexing. However, directional transmission introduces two problems: deafness and directional hidden terminals problems. We observe that these problems result in saturation throughput disparity among the competing flows in directional CSMA/CA based Ad hoc networks and bring challenges for modeling the saturation throughput of the flows. In this article, we concentrate on how to model and analyze the saturation throughput disparity of different flows in directional CSMA/CA based Ad hoc networks. We first divide the collisions occurring in the transmission process into directional instantaneous collisions and directional persistent collisions. Then we propose a four-dimensional Markov chain to analyze the transmission state for a specific node. Our model has three different kinds of processes, namely back-off process, transmission process and freezing process. Each process contains a certain amount of continuous time slots which is defined as the basic time unit of the directional CSMA/CA protocols and the time length of each slot is fixed. We characterize the collision probabilities of the node by the one-step transition probability matrix in our Markov chain model. Accordingly, we can finally deduce the saturation throughput for each directional data stream and evaluate saturation throughput disparity for a given network topology. Finally, we verify the accuracy of our model by comparing the deviation of analytical results and simulation results.

Development of a 3D Object Recognition Component for OPRoS (OPRoS를 위한 3차원 물체 인식 컴포넌트 개발)

  • Han, Chang-Ho;Oh, Choon-Suk
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.11 no.3
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    • pp.83-91
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    • 2011
  • Recently, many researchers in the world are concentrated to develop the robot platform which is to reduce the developing cost by reusing existing softwares. In this paper, we describe that the 3 dimension recognition object components for OPRoS (Open Platform for Robotic Services) which is developed in Korea. We present that the structure of the component, disparity map and depth map algorithm for recognizing 3 dimension space. We used stereo matching and block matching method to produce the disparity map. We test the component on the computer with OPRoS platform and show the results of accuracy and performance time.

Stereo Vision System Using Relative Stereo Disparity with Subpixel Resolution

  • Kim, Chi-Yen;Ahn, Cheol-Ki;Lee, Min-Cheol
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.407-407
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    • 2000
  • For acquisition of 3-Dimensional information in real space, stereo vision system is suitable. In the stereo system, 3D real world position is derived from translation of coordinates between cameras and world. Thus, to use stereo vision, it is needed to construct a precise system which provides kinematically precise translation between camera and world coordinate, in spite of intricacy and hardness. So much cost and time should be spent to build the system. In this paper, facilely to solve previous problem, a method which can easily obtain 3D informations using reference objects and RSD(Relative Stereo Disparity) is proposed. Instead of direct computation of position with translation of coordinates, only relative stereo disparity in stereo pair of image is used to find the reference depth of objects, and real 3D position is computed with initial condition of reference objects. In computation, subpixel resolution is involved to find the display for accuracy. To find the RSD, corresponding points are calculated in subpixel resolution. So the result in experiemnt will be shown that subpixel resolution is more accurate than 1 pixel resolution.

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A Technique for Building Occupancy Maps Using Stereo Depth Information and Its Application (스테레오 깊이 정보를 이용한 점유맵 구축 기법과 응용)

  • Kim, Nak-Hyun;Oh, Se-Jun
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.45 no.3
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    • pp.1-10
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    • 2008
  • An occupancy map is a representation methodology describing the region occupied by objects in 3D space, which can be utilized for autonomous navigation and object recognition. In this paper, we describe a technique for building an occupancy map using depth data extracted from stereo images. In addition, some techniques are proposed for utilizing the occupancy map for the segmentation of object regions. After the geometric information on the ground plane is extracted from a disparity image, the occupancy map is constructed by projecting each matched point to the ground plane-based 3D space. We explain techniques for extracting moving object regions using the occupancy map and present experimental results using real stereo images.

Active eye system for tracking a moving object (이동물체 추적을 위한 능동시각 시스템 구축)

  • 백문홍
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.257-259
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    • 1996
  • This paper presents the active eye system for tracking a moving object in 3D space. A prototype system able to track a moving object is designed and implemented. The mechanical system ables the control of platform that consists of binocular camera and also the control of the vergence angle of each camera by step motor. Each camera has two degrees of freedom. The image features of the object are extracted from complicated environment by using zero disparity filtering(ZDF). From the cnetroid of the image features the gaze point on object is calculated and the vergence angle of each camera is controlled by step motor. The Proposed method is implemented on the prototype with robust and fast calculation time.

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