• Title/Summary/Keyword: face tracking

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A study on the speed control of the step motor for driving face-tracking camera (얼굴추적 카메라 구동에 사용된 스텝모터의 속도제어에 관한 연구)

  • Lee, J.B.;Sung, H.K.;Kim, Y.O.;Jeong, J.H.;Bom, J.H.
    • Proceedings of the KIEE Conference
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    • 2001.10a
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    • pp.230-232
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    • 2001
  • The camera system we researched has two stepping motors for the pan and tilt operation, and the human face tracking algorithm. Recently, this kind of the camera is used in PC communication, telecommunication vision meeting and tele-lecture. This paper discusses the smooth speed control method of this camera when the face is moved to up, down, left and right direction. We used a mean shift algorithm for the face-tracking, proposed the speed control algorithm using a fuzzy logic and certified this characteristics with the experiment.

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Emergency Signal Detection based on Arm Gesture by Motion Vector Tracking in Face Area

  • Fayyaz, Rabia;Park, Dae Jun;Rhee, Eun Joo
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.12 no.1
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    • pp.22-28
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    • 2019
  • This paper presents a method for detection of an emergency signal expressed by arm gestures based on motion segmentation and face area detection in the surveillance system. The important indicators of emergency can be arm gestures and voice. We define an emergency signal as the 'Help Me' arm gestures in a rectangle around the face. The 'Help Me' arm gestures are detected by tracking changes in the direction of the horizontal motion vectors of left and right arms. The experimental results show that the proposed method successfully detects 'Help Me' emergency signal for a single person and distinguishes it from other similar arm gestures such as hand waving for 'Bye' and stretching. The proposed method can be used effectively in situations where people can't speak, and there is a language or voice disability.

Detection of Face Direction by Using Inter-Frame Difference

  • Jang, Bongseog;Bae, Sang-Hyun
    • Journal of Integrative Natural Science
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    • v.9 no.2
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    • pp.155-160
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    • 2016
  • Applying image processing techniques to education, the face of the learner is photographed, and expression and movement are detected from video, and the system which estimates degree of concentration of the learner is developed. For one learner, the measuring system is designed in terms of estimating a degree of concentration from direction of line of learner's sight and condition of the eye. In case of multiple learners, it must need to measure each concentration level of all learners in the classroom. But it is inefficient because one camera per each learner is required. In this paper, position in the face region is estimated from video which photographs the learner in the class by the difference between frames within the motion direction. And the system which detects the face direction by the face part detection by template matching is proposed. From the result of the difference between frames in the first image of the video, frontal face detection by Viola-Jones method is performed. Also the direction of the motion which arose in the face region is estimated with the migration length and the face region is tracked. Then the face parts are detected to tracking. Finally, the direction of the face is estimated from the result of face tracking and face parts detection.

Robot vision system for face tracking using color information from video images (로봇의 시각시스템을 위한 동영상에서 칼라정보를 이용한 얼굴 추적)

  • Jung, Haing-Sup;Lee, Joo-Shin
    • Journal of Advanced Navigation Technology
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    • v.14 no.4
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    • pp.553-561
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    • 2010
  • This paper proposed the face tracking method which can be effectively applied to the robot's vision system. The proposed algorithm tracks the facial areas after detecting the area of video motion. Movement detection of video images is done by using median filter and erosion and dilation operation as a method for removing noise, after getting the different images using two continual frames. To extract the skin color from the moving area, the color information of sample images is used. The skin color region and the background area are separated by evaluating the similarity by generating membership functions by using MIN-MAX values as fuzzy data. For the face candidate region, the eyes are detected from C channel of color space CMY, and the mouth from Q channel of color space YIQ. The face region is tracked seeking the features of the eyes and the mouth detected from knowledge-base. Experiment includes 1,500 frames of the video images from 10 subjects, 150 frames per subject. The result shows 95.7% of detection rate (the motion areas of 1,435 frames are detected) and 97.6% of good face tracking result (1,401 faces are tracked).

Face Tracking and Recognition on the arbitrary person using Nonliner Manifolds (비선형적 매니폴드를 이용한 임의 얼굴에 대한 얼굴 추적 및 인식)

  • Ju, Myung-Ho;Kang, Hang-Bong
    • 한국HCI학회:학술대회논문집
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    • 2008.02a
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    • pp.342-347
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    • 2008
  • Face tracking and recognition are difficult problems because the face is a non-rigid object. If the system tries to track or recognize the unknown face continuously, it can be more hard problems. In this paper, we propose the method to track and to recognize the face of the unknown person on video sequences using linear combination of nonlinear manifold models that is constructed in the system. The arbitrary input face has different similarities with different persons in system according to its shape or pose. Do we can approximate the new nonlinear manifold model for the input face by estimating the similarities with other faces statistically. The approximated model is updated at each frame for the input face. Our experimental results show that the proposed method is efficient to track and recognize for the arbitrary person.

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Design and Implementation of Driving System for Face Tracking Camera using Fuzzy Control (퍼지제어를 이용한 얼굴추적 카메라 구동 시스템의 설계 및 구현)

  • 이종배;임준홍
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.40 no.3
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    • pp.127-134
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    • 2003
  • In this paper, the speed control problem of moving camera is investigated for tracking the movement of the human-face. The camera system with pan-tilt mechanism sends an image to PC and PC sends back tracking coordinate to the camera. Then the camera tracks a human face in real time. The speed of the stepping motors for moving the camera must be controlled to the target region fast enough and smoothly, In this paper, a fuzzy logic controller is proposed for driving step motors. By creating driving acceleration and deceleration speed Profile, the speed of the motors is controled fast and smoothly. Experiments are performed to show the effectiveness of the proposed method.

Real-time Tracking and Identification for Multi-Camera Surveillance System

  • Hong, Yo-Hoon;Song, Seung June;Rho, Jungkyu
    • International Journal of Internet, Broadcasting and Communication
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    • v.10 no.1
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    • pp.16-22
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    • 2018
  • This paper presents a solution for personal profiling system based on user-oriented tracking. Here, we introduce a new way to identify and track humans by using two types of cameras: dome and face camera. Dome camera has a wide view angle so that it is suitable for tracking human movement in large area. However, it is difficult to identify a person only by using dome camera because it only sees the target from above. Thus, face camera is employed to obtain facial information for identifying a person. In addition, we also propose a new mechanism to locate human on targeted location by using grid-cell system. These result in a system which has the capability of maintaining human identity and tracking human activity (movement) effectively.

A Movement Tracking Model for Non-Face-to-Face Excercise Contents (비대면 운동 콘텐츠를 위한 움직임 추적 모델)

  • Chung, Daniel;Cho, Mingu;Ko, Ilju
    • KIPS Transactions on Computer and Communication Systems
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    • v.10 no.6
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    • pp.181-190
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    • 2021
  • Sports activities conducted by multiple people are difficult to proceed in a situation where a widespread epidemic such as COVID-19 is spreading, and this causes a lack of physical activity in modern people. This problem can be overcome by using online exercise contents, but it is difficult to check detailed postures such as during face-to-face exercise. In this study, we present a model that detects posture and tracks movement using IT system for better non-face-to-face exercise content management. The proposed motion tracking model defines a body model with reference to motion analysis methods widely used in physical education and defines posture and movement accordingly. Using the proposed model, it is possible to recognize and analyze movements used in exercise, know the number of specific movements in the exercise program, and detect whether or not the exercise program is performed. In order to verify the validity of the proposed model, we implemented motion tracking and exercise program tracking programs using Azure Kinect DK, a markerless motion capture device. If the proposed motion tracking model is improved and the performance of the motion capture system is improved, more detailed motion analysis is possible and the number of types of motions can be increased.

Multiple Face Tracking System Using the Kalman Estimator Based on the Color SSD Algorithm (컬러 SSD 알고리즘 기반 칼만 예측기를 이용한 다수의 얼굴 검출 및 추적 시스템)

  • Kim, Byoung-Ki;Han, Young-Joon;Hahn, Hern-Soo
    • Proceedings of the IEEK Conference
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    • 2005.11a
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    • pp.347-350
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    • 2005
  • This paper proposes a new tracking algorithm using the Kalman estimator based color SSD algorithm. The Kalman estimator includes the color information as well as the position and size of the face region in its state vector, to take care of the variation of skin color while faces are moving. Based on the estimated face position, the color SSD algorithm finds the face matching with the one in the previous frame even when the color and size of the face region vary. The features of a face region extracted by the color SSD algorithm are used to update the state of the Kalman estimator.

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Face Tracking and Recognition in Video with PCA-based Pose-Classification and (2D)2PCA recognition algorithm (비디오속의 얼굴추적 및 PCA기반 얼굴포즈분류와 (2D)2PCA를 이용한 얼굴인식)

  • Kim, Jin-Yul;Kim, Yong-Seok
    • Journal of the Korean Institute of Intelligent Systems
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    • v.23 no.5
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    • pp.423-430
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    • 2013
  • In typical face recognition systems, the frontal view of face is preferred to reduce the complexity of the recognition. Thus individuals may be required to stare into the camera, or the camera should be located so that the frontal images are acquired easily. However these constraints severely restrict the adoption of face recognition to wide applications. To alleviate this problem, in this paper, we address the problem of tracking and recognizing faces in video captured with no environmental control. The face tracker extracts a sequence of the angle/size normalized face images using IVT (Incremental Visual Tracking) algorithm that is known to be robust to changes in appearance. Since no constraints have been imposed between the face direction and the video camera, there will be various poses in face images. Thus the pose is identified using a PCA (Principal Component Analysis)-based pose classifier, and only the pose-matched face images are used to identify person against the pre-built face DB with 5-poses. For face recognition, PCA, (2D)PCA, and $(2D)^2PCA$ algorithms have been tested to compute the recognition rate and the execution time.