• 제목/요약/키워드: the object

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Color Object Recognition and Real-Time Tracking using Neural Networks

  • Choi, Dong-Sun;Lee, Min-Jung;Choi, Young-Kiu
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.135-135
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    • 2001
  • In recent years there have been increasing interests in real-time object tracking with image information. Since image information is affected by illumination, this paper presents the real-time object tracking method based on neural networks that have robust characteristics under various illuminations. This paper proposes three steps to track the object and the fast tracking method. In the first step the object color is extracted using neural networks. In the second step we detect the object feature information based on invariant moment. Finally the object is tracked through a shape recognition using neural networks. To achieve the fast tracking performance, we have a global search for entire image and then have tracking the object through local search when the object is recognized.

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A Novel Approach for Object Detection in Illuminated and Occluded Video Sequences Using Visual Information with Object Feature Estimation

  • Sharma, Kajal
    • IEIE Transactions on Smart Processing and Computing
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    • 제4권2호
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    • pp.110-114
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    • 2015
  • This paper reports a novel object-detection technique in video sequences. The proposed algorithm consists of detection of objects in illuminated and occluded videos by using object features and a neural network technique. It consists of two functional modules: region-based object feature extraction and continuous detection of objects in video sequences with region features. This scheme is proposed as an enhancement of the Lowe's scale-invariant feature transform (SIFT) object detection method. This technique solved the high computation time problem of feature generation in the SIFT method. The improvement is achieved by region-based feature classification in the objects to be detected; optimal neural network-based feature reduction is presented in order to reduce the object region feature dataset with winner pixel estimation between the video frames of the video sequence. Simulation results show that the proposed scheme achieves better overall performance than other object detection techniques, and region-based feature detection is faster in comparison to other recent techniques.

An Efficient Method of Scanning and Tracking for AR

  • Park, Yerang;Chin, Seongah
    • International Journal of Advanced Culture Technology
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    • 제7권4호
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    • pp.302-307
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    • 2019
  • In this paper, we propose an efficient method for AR toolkit Vuforia. In order to increase the scan rate when using the 3D object scanner, the scan rate parameters need to be analyzed in terms of the angle and distance. In addition, in order to increase the tracking rate when tracking an object, the tracking rate has to be evaluated according to the position, complexity, and contrast of the object. To this end, we have defined the difference of scan rate according to angle and distance between camera and object when using object scanner and the recognition time according to object's position, complexity and contrast when tracking object.

Advanced Bounding Box Prediction With Multiple Probability Map

  • Lee, Poo-Reum;Kim, Yoon
    • 한국컴퓨터정보학회논문지
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    • 제22권12호
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    • pp.63-68
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    • 2017
  • In this paper, we propose a bounding box prediction algorithm using multiple probability maps to improve object detection result of object detector. Although the performance of object detectors has been significantly improved, it is still not perfect due to technical problems and lack of learning data. Therefore, we use the result correction method to obtain more accurate object detection results. In the proposed algorithm, the preprocessed bounding box created as a result of object detection by the object detector is clustered in various form, and a conditional probability is given to each cluster to make multiple probability map. Finally, multiple probability map create new bounding box of object using morphological elements. Experiment results show that the newly predicted bounding box reduces the error in ground truth more than 45% on average compared to the previous bounding box.

인공지능 객체인식에 관한 파라미터 측정 연구 (A Study On Parameter Measurement for Artificial Intelligence Object Recognition)

  • 최병관
    • 디지털산업정보학회논문지
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    • 제15권3호
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    • pp.15-28
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    • 2019
  • Artificial intelligence is evolving rapidly in the ICT field, smart convergence media system and content industry through the fourth industrial revolution, and it is evolving very rapidly through Big Data. In this paper, we propose a face recognition method based on object recognition based on object recognition through artificial intelligence. In this method, Were experimented and studied through the object recognition technique of artificial intelligence. In the conventional 3D image field, general research on object recognition has been carried out variously, and researches have been conducted on the side effects of visual fatigue and dizziness through 3D image. However, in this study, we tried to solve the problem caused by the quantitative difference between object recognition and object recognition for human factor algorithm that measure visual fatigue through cognitive function, morphological analysis and object recognition. Especially, The new method of computer interaction is presented and the results are shown through experiments.

모멘트 변화와 객체 크기 비율을 이용한 객체 행동 및 위험상황 인식 (Object-Action and Risk-Situation Recognition Using Moment Change and Object Size's Ratio)

  • 곽내정;송특섭
    • 한국멀티미디어학회논문지
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    • 제17권5호
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    • pp.556-565
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    • 2014
  • This paper proposes a method to track object of real-time video transferred through single web-camera and to recognize risk-situation and human actions. The proposed method recognizes human basic actions that human can do in daily life and finds risk-situation such as faint and falling down to classify usual action and risk-situation. The proposed method models the background, obtains the difference image between input image and the modeled background image, extracts human object from input image, tracts object's motion and recognizes human actions. Tracking object uses the moment information of extracting object and the characteristic of object's recognition is moment's change and ratio of object's size between frames. Actions classified are four actions of walking, waling diagonally, sitting down, standing up among the most actions human do in daily life and suddenly falling down is classified into risk-situation. To test the proposed method, we applied it for eight participants from a video of a web-cam, classify human action and recognize risk-situation. The test result showed more than 97 percent recognition rate for each action and 100 percent recognition rate for risk-situation by the proposed method.

약속된 제스처를 이용한 객체 인식 및 추적 (Object Detection Using Predefined Gesture and Tracking)

  • 배대희;이준환
    • 한국컴퓨터정보학회논문지
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    • 제17권10호
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    • pp.43-53
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    • 2012
  • 본 논문에서는 화면상 약속된 동작을 찾고 추적하는 알고리즘을 이용한 사용자 인터페이스를 제안한다. 현재 frame과 복수의 이전 frame간의 차영상을 이용하여 움직임 영역을 검출하고 약속된 제스처를 취하는 영역을 제어대상으로 인식한다. 이를 통하여 사용자가 장갑을 사용한다던지, 인종, 피부색등에 구애받지 않고 손동작 영역을 검출해 낼 수 있다. 또한 기존 색체 분포 추적 알고리즘을 개량하여 유사한 배경을 가로지르는 경우의 무게중심 위치의 정확성을 높였다. 그 결과 기존 피부색 인식 방법에 비해 약속된 손동작 인식률의 향상이 있었으며 기존 색체 추적 알고리즘에 비교하여 추적 인식률 향상을 확인할 수 있었다.

능동 복제 기반 CORBA 객체 그룹 지원 (Supporting CORBA Object Group based on Active Replication)

  • 손덕주;신범주;남궁한;진성일
    • 한국정보처리학회논문지
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    • 제6권11S호
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    • pp.3340-3349
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    • 1999
  • Supporting object group on distributed object system give merits such as load balancing, fault tolerance and high availability. In this paper, we describe a CORBA ORB that has been designed to support object group based on active replication. The ORB supports the operational model in which it uses the IIOP for communication between client and server and total ordered multicast protocol for consistency control among group members. And through extension of ORB, it provides functions required for support of object group. Since it provides transparency of object replication, the ORB is interoperable with the existing CORBA products. It make possible for existing server application to be easily extended to application supporting object group as adding interface functions which should be used for building applications is minimized. A prototype is implemented, and performance of the replicated object group is tested and compared with a single object invocation.

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센서 정보를 이용한 객체 추적에 대한 연구 (A study of object trace using sensor information)

  • 김관중
    • 한국산학기술학회논문지
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    • 제14권4호
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    • pp.1921-1925
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    • 2013
  • 본 논문에서는 일정 지역에 내에 진입한 영상 객체에 대한 객체추적 방안을 제안한다. 인식된 객체에 대한 추적은 객체가 특정 지역에 진입할 경우 객체의 이동 패턴을 탐지하기 위해 추적을 수행할 수 있다. 이는 여러 애플리케이션에 적용될 수 있는 것으로 위험 지역 혹은 경계 지역에 비인가 객체의 침입이나 특정 객체의 행동 패턴을 확인하기 위하여 객체의 추적 및 탐색을 수행하는 것이다.

비디오 감시 시스템에서 실시간 움직이는 물체 검출 및 그림자 제거 (Real-Time Moving Object Detection and Shadow Removal in Video Surveillance System)

  • 이영숙;정완영
    • 한국정보통신학회:학술대회논문집
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    • 한국해양정보통신학회 2009년도 추계학술대회
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    • pp.574-578
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    • 2009
  • 정지 영상이나 비디오 영상 시퀀스에서 배경 영상으로부터 움직이는 관심 물체를 구별하기 위한 실시간 물체 검출은 물체의 위치 추적과 인식에 있어 필수적인 단계이다. 물체 분할 후에 그림자 영역이 움직이는 물체 영역에 포함되어지기 때문에 그림자는 물체의 일부분 혹은 움직이는 물체로 오분류될 수 있다. 이러한 이유로 그림자 제거 알고리즘은 움직이는 물체 검출 및 추적 시스템의 결과에 중요한 역할을 한다. 이 문제점들을 해결하기 위해 본 논문에서는 움직이는 물체의 특징과 색상공간에서 그림자의 특징에 기반을 둔 정확한 물체 검출과 그림자 제거 알고리즘을 제안한다. 실험결과는 제안 알고리즘이 실험 영상에서 물체 검출과 그림자 제거에 대해 효과적인 것을 알 수가 있다.

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