• Title/Summary/Keyword: CAMSHIFT algorithm

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Object-Tracking System Using Combination of CAMshift and Kalman filter Algorithm (CAMshift 기법과 칼만 필터를 결합한 객체 추적 시스템)

  • Kim, Dae-Young;Park, Jae-Wan;Lee, Chil-Woo
    • Journal of Korea Multimedia Society
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    • v.16 no.5
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    • pp.619-628
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    • 2013
  • In this paper, we describe a strongly improved tracking method using combination of CAMshift and Kalman filter algorithm. CAMshift algorithm doesn't consider the object's moving direction and velocity information when it set the search windows for tracking. However if Kalman filter is combined with CAMshift for setting the search window, it can accurately predict the object's location with the object's present location and velocity information. By using this prediction before CAMshift algorithm, we can track fast moving objects successfully. Also in this research, we show better tracking results than conventional approaches which make use of single color information by using both color information of HSV and YCrCb simultaneously. This modified approach obtains more robust color segmentation than others using single color information.

PTZ Camera Tracking Using CAMShift (CAMShift를 이용한 PTZ 카메라 추적)

  • Chang, Il-Sik;An, Tae-Ki;Park, Kwang-Young;Park, Goo-Man
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.35 no.3C
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    • pp.271-277
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    • 2010
  • In this paper we proposed an object tracking system using PTZ camera. Once the target object is detected, the CAMshift tracking algorithm focuses it in realtime mode as the camera is moving accordingly. Since the CAMShift algorithm takes into account the object size, zoom related tracking is possible. We used the spherical coordinate to gain pan and tilt position. The position information is used to set the center of target object in the middle of the image by using the PTZ protocol and RS-485 interface. Our system showed excellent experimental results in various environments.

A Moving Object Tracking using Color and OpticalFlow Information (컬러 및 광류정보를 이용한 이동물체 추적)

  • Kim, Ju-Hyeon;Choi, Han-Go
    • Journal of the Institute of Convergence Signal Processing
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    • v.15 no.4
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    • pp.112-118
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    • 2014
  • This paper deals with a color-based tracking of a moving object. Firstly, existing Camshift algorithm is complemented to improve the tracking weakness in the brightness change of an image which occurs in every frame. The complemented Camshift still shows unstable tracking when the objects with same color of the tracking object exist in background. In order to overcome the drawback this paper proposes the Camshift combined with KLT algorithm based on optical flow. The KLT algorithm performing the pixel-based feature tracking can complement the shortcoming of Camshift. Experimental results show that the merged tracking method makes up for the drawback of the Camshit algorithm and also improves tracking performance.

Robust Tracking Algorithm for Moving Object using Kalman Filter and Variable Search Window Technique (칼만 필터와 가변적 탐색 윈도우 기법을 적용한 강인한 이동 물체 추적 알고리즘)

  • Kim, Young-Kyun;Hyeon, Byeong-Yong;Cho, Young-Wan;Seo, Ki-Sung
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.7
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    • pp.673-679
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    • 2012
  • This paper introduces robust tracking algorithm for fast and erratic moving object. CAMSHIFT algorithm has less computation and efficient performance for object tracking. However, the method fails to track a object if it moves out of search window by fast velocity and/or large movement. The size of the search window in CAMSHIFT algorithm should be selected manually also. To solve these problems, we propose an efficient prediction technique for fast movement of object using Kalman Filter with automatic initial setting and variable configuration technique for search window. The proposed method is compared to the traditional CAMSHIFT algorithm for searching and tracking performance of objects on test image frames.

Efficient Text Localization using MLP-based Texture Classification (신경망 기반의 텍스춰 분석을 이용한 효율적인 문자 추출)

  • Jung, Kee-Chul;Kim, Kwang-In;Han, Jung-Hyun
    • Journal of KIISE:Software and Applications
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    • v.29 no.3
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    • pp.180-191
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    • 2002
  • We present a new text localization method in images using a multi-layer perceptron(MLP) and a multiple continuously adaptive mean shift (MultiCAMShift) algorithm. An automatically constructed MLP-based texture classifier generates a text probability image for various types of images without an explicit feature extraction. The MultiCAMShift algorithm, which operates on the text probability Image produced by an MLP, can place bounding boxes efficiently without analyzing the texture properties of an entire image.

Real-Time Human Tracking Using Skin Area and Modified Multi-CAMShift Algorithm (피부색과 변형된 다중 CAMShift 알고리즘을 이용한 실시간 휴먼 트래킹)

  • Min, Jae-Hong;Kim, In-Gyu;Baek, Joong-Hwan
    • Journal of Advanced Navigation Technology
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    • v.15 no.6
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    • pp.1132-1137
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    • 2011
  • In this paper, we propose Modified Multi CAMShift Algorithm(Modified Multi Continuously Adaptive Mean Shift Algorithm) that extracts skin color area and tracks several human body parts for real-time human tracking system. Skin color area is extracted by filtering input image in predefined RGB value range. These areas are initial search windows of hands and face for tracking. Gaussian background model prevents search window expending because it restricts skin color area. Also when occluding between these areas, we give more weights in occlusion area and move mass center of target area in color probability distribution image. As result, the proposed algorithm performs better than the original CAMShift approach in multiple object tracking and even when occluding of objects with similar colors.

Human Body Tracking and Pose Estimation Using CamShift Based on Kalman Filter and Weighted Search Windows (칼만 필터와 가중탐색영역 CAMShift를 이용한 휴먼 바디 트래킹 및 자세추정)

  • Min, Jae-Hong;Kim, In-Gyu;Hwang, Seung-Jun;Baek, Joong-Hwan
    • Journal of Advanced Navigation Technology
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    • v.16 no.3
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    • pp.545-552
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    • 2012
  • In this paper, we propose Modified Multi CAMShift Algorithm based on Kalman filter and Weighted Search Windows(KWMCAMShift) that extracts skin color area and tracks several human body parts for real-time human tracking system. We propose modified CAMShift algorithm that generates background model, extracts skin area of hands and head, and tracks the body parts. Kalman filter stabilizes tracking search window of skin area due to changing skin area in consecutive frames. Each occlusion areas is avoided by using weighted window of non-search areas and main-search area. And shadows are eliminated from background model and intensity of shadow. The proposed KWMCAMShift algorithm can estimate human pose in real-time and achieves 96.82% accuracy even in the case of occlusions.

Implementation of Finger-Gesture Game Controller using CAMShift and Double Circle Tracing Method (CAMShift와 이중 원형 추적법을 이용한 손 동작 게임 컨트롤러 구현)

  • Lee, Woo-Beom
    • Journal of the Institute of Convergence Signal Processing
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    • v.15 no.2
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    • pp.42-47
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    • 2014
  • A finger-gesture game controller using the single camera is implemented in this paper, which is based on the recognition of the number of fingers and the index finger moving direction. Proposed method uses the CAMShift algorithm to trace the end-point of index finger effectively. The number of finger is recognized by using a double circle tracing method. Then, HSI color mode transformation is performed for the CAMShift algorithm, and YCbCr color model is used in the double circle tracing method. Also, all processing tasks are implemented by using the Intel OpenCV library and C++ language. In order to evaluate the performance of the proposed method, we developed a shooting game simulator and validated the proposed method. The proposed method showed the average recognition ratio of more than 90% for each of the game command-mode.

Implementation of Improved Object Detection and Tracking based on Camshift and SURF for Augmented Reality Service (증강현실 서비스를 위한 Camshift와 SURF를 개선한 객체 검출 및 추적 구현)

  • Lee, Yong-Hwan;Kim, Heung-Jun
    • Journal of the Semiconductor & Display Technology
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    • v.16 no.4
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    • pp.97-102
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    • 2017
  • Object detection and tracking have become one of the most active research areas in the past few years, and play an important role in computer vision applications over our daily life. Many tracking techniques are proposed, and Camshift is an effective algorithm for real time dynamic object tracking, which uses only color features, so that the algorithm is sensitive to illumination and some other environmental elements. This paper presents and implements an effective moving object detection and tracking to reduce the influence of illumination interference, which improve the performance of tracking under similar color background. The implemented prototype system recognizes object using invariant features, and reduces the dimension of feature descriptor to rectify the problems. The experimental result shows that that the system is superior to the existing methods in processing time, and maintains better problem ratios in various environments.

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AdaBoost-based Real-Time Face Detection & Tracking System (AdaBoost 기반의 실시간 고속 얼굴검출 및 추적시스템의 개발)

  • Kim, Jeong-Hyun;Kim, Jin-Young;Hong, Young-Jin;Kwon, Jang-Woo;Kang, Dong-Joong;Lho, Tae-Jung
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.11
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    • pp.1074-1081
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    • 2007
  • This paper presents a method for real-time face detection and tracking which combined Adaboost and Camshift algorithm. Adaboost algorithm is a method which selects an important feature called weak classifier among many possible image features by tuning weight of each feature from learning candidates. Even though excellent performance extracting the object, computing time of the algorithm is very high with window size of multi-scale to search image region. So direct application of the method is not easy for real-time tasks such as multi-task OS, robot, and mobile environment. But CAMshift method is an improvement of Mean-shift algorithm for the video streaming environment and track the interesting object at high speed based on hue value of the target region. The detection efficiency of the method is not good for environment of dynamic illumination. We propose a combined method of Adaboost and CAMshift to improve the computing speed with good face detection performance. The method was proved for real image sequences including single and more faces.