• Title, Summary, Keyword: hand tracking

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Hand Region Segmentation and Tracking Based on Hue Image (Hue 영상을 기반한 손 영역 검출 및 추적)

  • 권화중;이준호
    • Proceedings of the IEEK Conference
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    • pp.1003-1006
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    • 1999
  • Hand segmentation and tracking is essential to the development of a hand gesture recognition system. This research features segementation and tracking of hand regions based the hue component of color. We propose a method that employs HSI color model, and segments and tracks hand regions using the hue component of color alone. In order to track the segmented hand regions, we only apply Kalman filter to a region of interest represented by a rectangle region. Initial experimental results show that the system accurately segments and tracks hand regions although it only uses the hue compoent of color. The system yields near real time throghput of 8 frames per second on a Pentium II 233MHz PC.

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Vision-based hand Gesture Detection and Tracking System (비전 기반의 손동작 검출 및 추적 시스템)

  • Park Ho-Sik;Bae Cheol-soo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.12C
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    • pp.1175-1180
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    • 2005
  • We present a vision-based hand gesture detection and tracking system. Most conventional hand gesture recognition systems utilize a simpler method for hand detection such as background subtractions with assumed static observation conditions and those methods are not robust against camera motions, illumination changes, and so on. Therefore, we propose a statistical method to recognize and detect hand regions in images using geometrical structures. Also, Our hand tracking system employs multiple cameras to reduce occlusion problems and non-synchronous multiple observations enhance system scalability. In this experiment, the proposed method has recognition rate of $99.28\%$ that shows more improved $3.91\%$ than the conventional appearance method.

The input device system with hand motion using hand tracking technique of CamShift algorithm (CamShift 알고리즘의 Hand Tracking 기법을 응용한 Hand Motion 입력 장치 시스템)

  • Jeon, Yu-Na;Kim, Soo-Ji;Lee, Chang-Hoon;Kim, Hyeong-Ryul;Lee, Sung-Koo
    • Journal of Digital Contents Society
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    • v.16 no.1
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    • pp.157-164
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    • 2015
  • The existing input device is limited to keyboard and mouse. However, recently new type of input device has been developed in response to requests from users. To reflect this trend we propose the new type of input device that gives instruction as analyzing the hand motion of image without special device. After binarizing the skin color area using Cam-Shift method and tracking, it recognizes the hand motion by inputting the finger areas and the angles from the palm center point, which are separated through labeling, into four cardinal directions and counting them. In cases when specific background was not set and without gloves, the recognition rate remained approximately at 75 percent. However, when specific background was set and the person wore red gloves, the recognition rate increased to 90.2 percent due to reduction in noise.

Real-Time Two Hands Tracking System

  • Liu, Nianjun;Lovell, Brian C.
    • Proceedings of the IEEK Conference
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    • pp.1491-1494
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    • 2002
  • The paper introduces a novel system of two hands real-time tracking based on the unrestricted hand skin segmentation by multi color systems. After corer-based segmentation and pre-processing operation, a label set of regions is created to locate the two hands automatically. By the normalization, template matching is used to find out the left or right hand. An improved fast self-adaptive tracking algorithm is applied and Canny filter is used for hand detection.

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A Hand Gesture Recognition System using 3D Tracking Volume Restriction Technique (3차원 추적영역 제한 기법을 이용한 손 동작 인식 시스템)

  • Kim, Kyung-Ho;Jung, Da-Un;Lee, Seok-Han;Choi, Jong-Soo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.6
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    • pp.201-211
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    • 2013
  • In this paper, we propose a hand tracking and gesture recognition system. Our system employs a depth capture device to obtain 3D geometric information of user's bare hand. In particular, we build a flexible tracking volume and restrict the hand tracking area, so that we can avoid diverse problems caused by conventional object detection/tracking systems. The proposed system computes running average of the hand position, and tracking volume is actively adjusted according to the statistical information that is computed on the basis of uncertainty of the user's hand motion in the 3D space. Once the position of user's hand is obtained, then the system attempts to detect stretched fingers to recognize finger gesture of the user's hand. In order to test the proposed framework, we built a NUI system using the proposed technique, and verified that our system presents very stable performance even in the case that multiple objects exist simultaneously in the crowded environment, as well as in the situation that the scene is occluded temporarily. We also verified that our system ensures running speed of 24-30 frames per second throughout the experiments.

Dynamic Manipulation of a Virtual Object in Marker-less AR system Based on Both Human Hands

  • Chun, Jun-Chul;Lee, Byung-Sung
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.4 no.4
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    • pp.618-632
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    • 2010
  • This paper presents a novel approach to control the augmented reality (AR) objects robustly in a marker-less AR system by fingertip tracking and hand pattern recognition. It is known that one of the promising ways to develop a marker-less AR system is using human's body such as hand or face for replacing traditional fiducial markers. This paper introduces a real-time method to manipulate the overlaid virtual objects dynamically in a marker-less AR system using both hands with a single camera. The left bare hand is considered as a virtual marker in the marker-less AR system and the right hand is used as a hand mouse. To build the marker-less system, we utilize a skin-color model for hand shape detection and curvature-based fingertip detection from an input video image. Using the detected fingertips the camera pose are estimated to overlay virtual objects on the hand coordinate system. In order to manipulate the virtual objects rendered on the marker-less AR system dynamically, a vision-based hand control interface, which exploits the fingertip tracking for the movement of the objects and pattern matching for the hand command initiation, is developed. From the experiments, we can prove that the proposed and developed system can control the objects dynamically in a convenient fashion.

Object Tracking Framework of Video Surveillance System based on Non-overlapping Multi-camera (비겹침 다중 IP 카메라 기반 영상감시시스템의 객체추적 프레임워크)

  • Han, Min-Ho;Park, Su-Wan;Han, Jong-Wook
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.21 no.6
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    • pp.141-152
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    • 2011
  • Growing efforts and interests of security techniques in a diverse surveillance environment, the intelligent surveillance system, which is capable of automatically detecting and tracking target objects in multi-cameras environment, is actively developing in a security community. In this paper, we propose an effective visual surveillance system that is avaliable to track objects continuously in multiple non-overlapped cameras. The proposed object tracking scheme consists of object tracking module and tracking management module, which are based on hand-off scheme and protocol. The object tracking module, runs on IP camera, provides object tracking information generation, object tracking information distribution and similarity comparison function. On the other hand, the tracking management module, runs on video control server, provides realtime object tracking reception, object tracking information retrieval and IP camera control functions. The proposed object tracking scheme allows comprehensive framework that can be used in a diverse range of application, because it doesn't rely on the particular surveillance system or object tracking techniques.

Enhanced Sign Language Transcription System via Hand Tracking and Pose Estimation

  • Kim, Jung-Ho;Kim, Najoung;Park, Hancheol;Park, Jong C.
    • Journal of Computing Science and Engineering
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    • v.10 no.3
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    • pp.95-101
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    • 2016
  • In this study, we propose a new system for constructing parallel corpora for sign languages, which are generally under-resourced in comparison to spoken languages. In order to achieve scalability and accessibility regarding data collection and corpus construction, our system utilizes deep learning-based techniques and predicts depth information to perform pose estimation on hand information obtainable from video recordings by a single RGB camera. These estimated poses are then transcribed into expressions in SignWriting. We evaluate the accuracy of hand tracking and hand pose estimation modules of our system quantitatively, using the American Sign Language Image Dataset and the American Sign Language Lexicon Video Dataset. The evaluation results show that our transcription system has a high potential to be successfully employed in constructing a sizable sign language corpus using various types of video resources.

The Estimation of Hand Pose Based on Mean-Shift Tracking Using the Fusion of Color and Depth Information for Marker-less Augmented Reality (비마커 증강현실을 위한 색상 및 깊이 정보를 융합한 Mean-Shift 추적 기반 손 자세의 추정)

  • Lee, Sun-Hyoung;Hahn, Hern-Soo;Han, Young-Joon
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.7
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    • pp.155-166
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    • 2012
  • This paper proposes a new method of estimating the hand pose through the Mean-Shift tracking algorithm using the fusion of color and depth information for marker-less augmented reality. On marker-less augmented reality, the most of previous studies detect the hand region using the skin color from simple experimental background. Because finger features should be detected on the hand, the hand pose that can be measured from cameras is restricted considerably. However, the proposed method can easily detect the hand pose from complex background through the new Mean-Shift tracking method using the fusion of the color and depth information from 3D sensor. The proposed method of estimating the hand pose uses the gravity point and two random points on the hand without largely constraints. The proposed Mean-Shift tracking method has about 50 pixels error less than general tracking method just using color value. The augmented reality experiment of the proposed method shows results of its performance being as good as marker based one on the complex background.

Hand Region Tracking and Fingertip Detection based on Depth Image (깊이 영상 기반 손 영역 추적 및 손 끝점 검출)

  • Joo, Sung-Il;Weon, Sun-Hee;Choi, Hyung-Il
    • Journal of the Korea Society of Computer and Information
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    • v.18 no.8
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    • pp.65-75
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    • 2013
  • This paper proposes a method of tracking the hand region and detecting the fingertip using only depth images. In order to eliminate the influence of lighting conditions and obtain information quickly and stably, this paper proposes a tracking method that relies only on depth information, as well as a method of using region growing to identify errors that can occur during the tracking process and a method of detecting the fingertip that can be applied for the recognition of various gestures. First, the closest point of approach is identified through the process of transferring the center point in order to locate the tracking point, and the region is grown from that point to detect the hand region and boundary line. Next, the ratio of the invalid boundary, obtained by means of region growing, is used to calculate the validity of the tracking region and thereby judge whether the tracking is normal. If tracking is normal, the contour line is extracted from the detected hand region and the curvature and RANSAC and Convex-Hull are used to detect the fingertip. Lastly, quantitative and qualitative analyses are performed to verify the performance in various situations and prove the efficiency of the proposed algorithm for tracking and detecting the fingertip.