• Title/Summary/Keyword: Detect3D

Search Result 824, Processing Time 0.038 seconds

Stereo Vision Based 3-D Motion Tracking for Human Animation

  • Han, Seung-Il;Kang, Rae-Won;Lee, Sang-Jun;Ju, Woo-Suk;Lee, Joan-Jae
    • Journal of Korea Multimedia Society
    • /
    • v.10 no.6
    • /
    • pp.716-725
    • /
    • 2007
  • In this paper we describe a motion tracking algorithm for 3D human animation using stereo vision system. This allows us to extract the motion data of the end effectors of human body by following the movement through segmentation process in HIS or RGB color model, and then blob analysis is used to detect robust shape. When two hands or two foots are crossed at any position and become disjointed, an adaptive algorithm is presented to recognize whether it is left or right one. And the real motion is the 3-D coordinate motion. A mono image data is a data of 2D coordinate. This data doesn't acquire distance from a camera. By stereo vision like human vision, we can acquire a data of 3D motion such as left, right motion from bottom and distance of objects from camera. This requests a depth value including x axis and y axis coordinate in mono image for transforming 3D coordinate. This depth value(z axis) is calculated by disparity of stereo vision by using only end-effectors of images. The position of the inner joints is calculated and 3D character can be visualized using inverse kinematics.

  • PDF

Human Head Mouse System Based on Facial Gesture Recognition

  • Wei, Li;Lee, Eung-Joo
    • Journal of Korea Multimedia Society
    • /
    • v.10 no.12
    • /
    • pp.1591-1600
    • /
    • 2007
  • Camera position information from 2D face image is very important for that make the virtual 3D face model synchronize to the real face at view point, and it is also very important for any other uses such as: human computer interface (face mouth), automatic camera control etc. We present an algorithm to detect human face region and mouth, based on special color features of face and mouth in $YC_bC_r$ color space. The algorithm constructs a mouth feature image based on $C_b\;and\;C_r$ values, and use pattern method to detect the mouth position. And then we use the geometrical relationship between mouth position information and face side boundary information to determine the camera position. Experimental results demonstrate the validity of the proposed algorithm and the Correct Determination Rate is accredited for applying it into practice.

  • PDF

Extracting a Regular Triangular Net for Offsetting (옵셋팅을 위한 정규 삼각망 추출)

  • Jung W.H.;Jeong C.S.;Shin H.Y.;Choi B.K.
    • Korean Journal of Computational Design and Engineering
    • /
    • v.9 no.3
    • /
    • pp.203-211
    • /
    • 2004
  • In this paper, we present a method of extracting a regular 2-manifold triangular net from a triangular net including degenerate and self-intersected triangles. This method can be applied to obtaining an offset model without degenerate and self-intersected triangles. Then this offset model can be used to generate CL curves and extract machining features for CAPP The robust and efficient algorithm to detect valid triangles by growing regions from an initial valid triangle is presented. The main advantage of the algorithm is that detection of valid triangles is performed only in valid regions and their adjacent selfintersections, and omitted in the rest regions (invalid regions). This advantage increases robustness of the algorithm. As well as a k-d tree bucketing method is used to detect self-intersections efficiently.

Automatic Detection of Left Ventricular Contour Using Hough Transform with Weighted Model from 2D Echocardiogram (가중모델 Hough 변환을 이용한 2D 심초음파도에서의 좌심실 윤곽선 자동 검출)

  • 김명남;조진호
    • Journal of Biomedical Engineering Research
    • /
    • v.15 no.3
    • /
    • pp.325-332
    • /
    • 1994
  • In this paper, a method is proposed to detect the endocardial contour of the left ventricle using the Hough transform with a weighted model and edge information from the 2D echocardiogram. The implementation of this method is as follows: first, an approximate model detection algorithm was implemented in order to detect the approximate endocardium model and the model center, then we constructed a weighted model with the detected model. Next, we found automatically the cavity center of the left ventricle performing the Hough transform which used the weighted model, and then we detected the endocardial contour using weighted model and edge image.

  • PDF

User Detection and Main Body Parts Estimation using Inaccurate Depth Information and 2D Motion Information (정밀하지 않은 깊이정보와 2D움직임 정보를 이용한 사용자 검출과 주요 신체부위 추정)

  • Lee, Jae-Won;Hong, Sung-Hoon
    • Journal of Broadcast Engineering
    • /
    • v.17 no.4
    • /
    • pp.611-624
    • /
    • 2012
  • 'Gesture' is the most intuitive means of communication except the voice. Therefore, there are many researches for method that controls computer using gesture input to replace the keyboard or mouse. In these researches, the method of user detection and main body parts estimation is one of the very important process. in this paper, we propose user objects detection and main body parts estimation method on inaccurate depth information for pose estimation. we present user detection method using 2D and 3D depth information, so this method robust to changes in lighting and noise and 2D signal processing 1D signals, so mainly suitable for real-time and using the previous object information, so more accurate and robust. Also, we present main body parts estimation method using 2D contour information, 3D depth information, and tracking. The result of an experiment, proposed user detection method is more robust than only using 2D information method and exactly detect object on inaccurate depth information. Also, proposed main body parts estimation method overcome the disadvantage that can't detect main body parts in occlusion area only using 2D contour information and sensitive to changes in illumination or environment using color information.

3-D Working Point Decision Method for Industrial Robot (산업용 로봇의 3차원 작업 위치 결정 방법)

  • Ryu, Hang-Ki;Lee, Jae-Kook;Kim, Byeong-Woo;Choi, Won-Ho
    • The Transactions of The Korean Institute of Electrical Engineers
    • /
    • v.57 no.1
    • /
    • pp.121-127
    • /
    • 2008
  • In this paper, we propose a new 3-D working point determination method for industrial robot using vision camera system and block interpolation technique with feature points in a vehicle body. To detect the feature points in a vehicle body, we applied the pattern matching method. For determination of working point, we applied block interpolation method. The block consists of 3-D type blocks with detected feature points per section. 3-D position is selected by Euclidean distance between 245 feature values and an acquired feature point. In order to evaluate the proposed algorithm, experiments are performed in glass equipment process in real industrial vehicle assembly line.

Combining Shape and SIFT Features for 3-D Object Detection and Pose Estimation (효과적인 3차원 객체 인식 및 자세 추정을 위한 외형 및 SIFT 특징 정보 결합 기법)

  • Tak, Yoon-Sik;Hwang, Een-Jun
    • The Transactions of The Korean Institute of Electrical Engineers
    • /
    • v.59 no.2
    • /
    • pp.429-435
    • /
    • 2010
  • Three dimensional (3-D) object detection and pose estimation from a single view query image has been an important issue in various fields such as medical applications, robot vision, and manufacturing automation. However, most of the existing methods are not appropriate in a real time environment since object detection and pose estimation requires extensive information and computation. In this paper, we present a fast 3-D object detection and pose estimation scheme based on surrounding camera view-changed images of objects. Our scheme has two parts. First, we detect images similar to the query image from the database based on the shape feature, and calculate candidate poses. Second, we perform accurate pose estimation for the candidate poses using the scale invariant feature transform (SIFT) method. We earned out extensive experiments on our prototype system and achieved excellent performance, and we report some of the results.

A Detection Algorithm Study of the Victim Signal for the DAA Regulation in MB-OFDM UWB System (MB-OFDM UWB 시스템에서 DAA 기술 기준 적용을 위한 피 간섭 신호 검출 방안 연구)

  • Shin, Cheol-Ho;Choi, Sang-Sung
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
    • /
    • v.20 no.12
    • /
    • pp.1297-1307
    • /
    • 2009
  • The purpose of this paper is to propose a detection algorithm and a tracking algorithm based on silent time using MB-OFDM UWB(Multi-Band Orthogonal Frequency Division Multiplexing Ultra Wide Band) receiver in order to satisfy DAA(Detect And Avoid) regulation of Korea to permit UWB in 3.1~4.8 GHz. In DAA regulation of Korea, if UWB device receives a signal more than -80 dBm/MHz from the victim system during UWB operation, the UWB system should avoid the collision within 2 sec. In this paper, we proposed the detection algorithm to detect the victim signal received by -80 dBm/MHz for the avoidance process that changes the operating UWB frequency to other UWB frequency and the subcarrier tracking algorithm to follow up the subcarrier positions of the victim signal for the tonenulling avoidance process that decreases the TX power of subcarriers occupied by the victim signal by -70 dBm/MHz. The performance of the detection algorithm and the tracking algorithm suggested in this paper is verified in simulation results considering various conditions.

Pitch Detection Using Variable LPF

  • Hong KEUM
    • Proceedings of the Acoustical Society of Korea Conference
    • /
    • 1994.06a
    • /
    • pp.963-970
    • /
    • 1994
  • In speech signal processing, it is very important to detect the pitch exactly. The algorithms for pitch extraction that have been proposed until now are not enough to detect the fine pitch in speech signal. Thus we propose the new algorithm which takes advantage of the G-peak extraction. It is the method to find MZCI(maximum zer-crossing interval) which is defined as cut-off bandwidth rate of LPF (low pass filter)and detect the pitch period of the voiced signals. This algorithm performs robustly with a gross error rate of 3.63% even in 0 dB SNR environment. The gross error rate for clean speech is only 0.18%. Also it is able to process all course with speed.

  • PDF

Accurate Parked Vehicle Detection using GMM-based 3D Vehicle Model in Complex Urban Environments (가우시안 혼합모델 기반 3차원 차량 모델을 이용한 복잡한 도시환경에서의 정확한 주차 차량 검출 방법)

  • Cho, Younggun;Roh, Hyun Chul;Chung, Myung Jin
    • The Journal of Korea Robotics Society
    • /
    • v.10 no.1
    • /
    • pp.33-41
    • /
    • 2015
  • Recent developments in robotics and intelligent vehicle area, bring interests of people in an autonomous driving ability and advanced driving assistance system. Especially fully automatic parking ability is one of the key issues of intelligent vehicles, and accurate parked vehicles detection is essential for this issue. In previous researches, many types of sensors are used for detecting vehicles, 2D LiDAR is popular since it offers accurate range information without preprocessing. The L shape feature is most popular 2D feature for vehicle detection, however it has an ambiguity on different objects such as building, bushes and this occurs misdetection problem. Therefore we propose the accurate vehicle detection method by using a 3D complete vehicle model in 3D point clouds acquired from front inclined 2D LiDAR. The proposed method is decomposed into two steps: vehicle candidate extraction, vehicle detection. By combination of L shape feature and point clouds segmentation, we extract the objects which are highly related to vehicles and apply 3D model to detect vehicles accurately. The method guarantees high detection performance and gives plentiful information for autonomous parking. To evaluate the method, we use various parking situation in complex urban scene data. Experimental results shows the qualitative and quantitative performance efficiently.