• Title/Summary/Keyword: motion estimation detection

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An algorithm for Video Object Detection using Multiresolution Motion Estimation (다해상도 움직임 예측을 이용한 동영상 물체탐지 알고리즘)

  • 조철훈;박장한;이한우;남궁재찬
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.40 no.1
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    • pp.87-95
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    • 2003
  • This paper proposes an object detection algorithm using the Multiresolution Motion Estimation(MRME) in wavelet d야main. A existing motion estimation method has characteristics of motion estimation but it requires having computation. Motion estimation in higher resolution used the motion vector of the lower resolution with the MRME that has parent-child relationship on wavelet coefficients. This method reduces the search area of motion estimation in higher resolution and computational complexity. The computational complexity of the proposed method is about 40% of the existing method using 3-level Set Partitioning in Hierarchical Trees(SPIHT) wavelet transform. The experimental results with the proposed method showed about 11% decrease of Mean Absolute Difference(MAD) and gains able to precise tracking of object.

A Technique of Image Depth Detection Using Motion Estimation and Object Tracking (모션 추정과 객체 추적을 이용한 이미지 깊이 검출기법)

  • Joh, Beom-Seok;Kim, Young-Ro
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.4 no.2
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    • pp.15-19
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    • 2008
  • In this paper, we propose a new algorithm of image depth detection using motion estimation and object tracking. In industry, robots are used for automobile, conveyer system, etc. But, these have much necessary time. Thus, in this paper, we develop the efficient method of image depth detection based on motion estimation and object tracking.

Motion Boundary Detection and Motion Vector Estimation by spatio-temporal Gradient Method using a New Spatial Gradient (새로운 공간경사를 사용한 시공간 경사법에 의한 운동경계 검출 및 이동벡터 추정)

  • 김이한;김성대
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.2
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    • pp.59-68
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    • 1993
  • The motion vector estimation and motion boundary detection have been briskly studied since they are an important clue for analysis of object structure and 3-d motion. The purpose of this researches is more exact estimation, but there are two main causes to make inaccurate. The one is the erroneous measurement of gradients in brightness values and the other is the blurring of motion boundries which is caused by the smoothness constraint. In this paper, we analyze the gradient measurement error of conventional methods and propose new technique based on it. When the proposed method is applied to the motion boundary detection in Schunck and motion vector estimation in Horn & Schunck, it is shown to have much better performance than conventional method is some artificial and real image sequences.

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Digital Image Stabilization Based on Edge Detection and Lucas-Kanade Optical Flow (Edge Detection과 Lucas-Kanade Optical Flow 방식에 기반한 디지털 영상 안정화 기법)

  • Lee, Hye-Jung;Choi, Yun-Won;Kang, Tae-Hun;Lee, Suk-Gyu
    • The Journal of Korea Robotics Society
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    • v.5 no.2
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    • pp.85-92
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    • 2010
  • In this paper, we propose a digital image stabilization technique using edge detection and Lucas-Kanade optical flow in order to minimize the motion of the shaken image. The accuracy of motion estimation based on block matching technique depends on the size of search window, which results in long calculation time. Therefore it is not applicable to real-time system. In addition, since the size of vector depends on that of block, it is difficult to estimate the motion which is bigger than the block size. The proposed method extracts the trust region using edge detection, to estimate the motion of some critical points in trust region based on Lucas-Kanade optical flow algorithm. The experimental results show that the proposed method stabilizes the shaking of motion image effectively in real time.

An adaptive motion estimation based on the temporal subband analysis (시간축 서브밴드 해석을 이용한 적응적 움직임 추정에 관한 연구)

  • 임중곤;정재호
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.6
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    • pp.1361-1369
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    • 1996
  • Motion estimation is one of the key components for high quality video coding. In this paper, a new motion estimation scheme for MPEG-like video coder is suggested. The proposed temporally adaptive motion estimation scheme consists of five functional blocks: Temporal subband analysis (TSBA), extraction of temporal information, scene change detection (SCD), picture type replacement (PTR), and temporally adapted block matching algorithm (TABMA). Here all the functional components are based on the temporal subband analysis. In this papre, we applied the analysis part of subband decompostion to the temporal axis of moving picture sequence, newly defined the temporal activity distribution (TAD) and average TAD, and proposed the temporally adapted block matching algorithm, the scene change detection algorithm and picture type replacement algorithm which employed the results of the temporal subband analysis. A new block matching algorithm TABMA is capable of controlling the block matching area. According to the temporal activity distribution of objects, it allocates the search areas nonuniformly. The proposed SCD and PTR can prevent unavailable motion prediction for abrupt scene changes. Computer simulation results show that the proposed motion estimation scheme improve the quality of reconstructed sequence and reduces the number of block matching trials to 40% of the numbers of trials in conventional methods. The TSBA based scene change detection algorithm can detect the abruptly changed scenes in the intentionally combined sequence of this experiment without additional computations.

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Preceding Vehicle Detection and Tracking with Motion Estimation by Radar-vision Sensor Fusion (레이더와 비전센서 융합기반의 움직임추정을 이용한 전방차량 검출 및 추적)

  • Jang, Jaehwan;Kim, Gyeonghwan
    • Journal of the Institute of Electronics and Information Engineers
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    • v.49 no.12
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    • pp.265-274
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    • 2012
  • In this paper, we propose a method for preceding vehicle detection and tracking with motion estimation by radar-vision sensor fusion. The motion estimation proposed results in not only correction of inaccurate lateral position error observed on a radar target, but also adaptive detection and tracking of a preceding vehicle by compensating the changes in the geometric relation between the ego-vehicle and the ground due to the driving. Furthermore, the feature-based motion estimation employed to lessen computational burden reduces the number of deployment of the vehicle validation procedure. Experimental results prove that the correction by the proposed motion estimation improves the performance of the vehicle detection and makes the tracking accurate with high temporal consistency under various road conditions.

The motion estimation algorithm implemented by the color / shape information of the object in the real-time image (실시간 영상에서 물체의 색/모양 정보를 이용한 움직임 검출 알고리즘 구현)

  • Kim, Nam-Woo;Hur, Chang-Wu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.11
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    • pp.2733-2737
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    • 2014
  • Motion detection according to the movement and the change area detection method according to the background difference and the motion history image for use in a motion estimation technique using a real-time image, the motion detection method according to the optical flow, the back-projection of the histogram of the object to track for motion tracking At the heart of MeanShift center point of the object and the object to track, while used, the size, and the like due to the motion tracking algorithm CamShift, Kalman filter to track with direction. In this paper, we implemented the motion detection algorithm based on color and shape information of the object and verify.

Nonlinear hierarchical motion estimation method based on decompositionof the functional domain (범함수 정의역 분할에 바탕을 둔 비선형 계층적 움직임 추정기법)

  • 심동규;박래홍
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.4
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    • pp.807-821
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    • 1996
  • In this paper, we proposed a nonlinear hierarchical mtion estimation method. Generally, the conventional hierarchical motion estimation methods have been proposed for fast convergence and detection of large motions. But they have a common drawback that large error in motion estimation is propapated across motion discontinuities. This artifiact is due to the constriaint of motion continuity and the linear interpolation of motion vectors between hierarchical levels. In this paper, we propose an effective hierarchical motion estimation mechod that is robust to motion discontinuities. The proposed algorithm is based on the decomposition of the functional domain for optimizing the intra-level motion estimation functional. Also, we propose an inter-level nonlinear motion estimation equation rather than using the conventional linearprojection scheme of motion field. computer simulations with several test sequences show tht the proposed algorithm performs better than several conventional methods.

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Motion Estimation-based Human Fall Detection for Visual Surveillance

  • Kim, Heegwang;Park, Jinho;Park, Hasil;Paik, Joonki
    • IEIE Transactions on Smart Processing and Computing
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    • v.5 no.5
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    • pp.327-330
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    • 2016
  • Currently, the world's elderly population continues to grow at a dramatic rate. As the number of senior citizens increases, detection of someone falling has attracted increasing attention for visual surveillance systems. This paper presents a novel fall-detection algorithm using motion estimation and an integrated spatiotemporal energy map of the object region. The proposed method first extracts a human region using a background subtraction method. Next, we applied an optical flow algorithm to estimate motion vectors, and an energy map is generated by accumulating the detected human region for a certain period of time. We can then detect a fall using k-nearest neighbor (kNN) classification with the previously estimated motion information and energy map. The experimental results show that the proposed algorithm can effectively detect someone falling in any direction, including at an angle parallel to the camera's optical axis.

Design and Verification of Algorithms for the Motion Detection of Vehicles using Hierarchical Motion Estimation and Parallel Processing (계층화 모션 추정법과 병렬처리 기반의 차량 움직임 측정 알고리즘 개발 및 검증1))

  • 강경훈;심현진;이은숙;정성태;남궁문;금기정;이상설
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.21-24
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    • 2002
  • This paper presents a new method for the motion detection of vehicles using hierarchical motion estimation and parallel processing. It captures the road image by using a CMOS sensor. It divides the captured image into small blocks and detects the motion of each block by using a block-matching method which is based on a hierarchical motion estimation and parallel processing for the real-time processing. The parallelism is achieved by using the pipeline and the data flow technique. The proposed method has been implemented with an embedded system. Experimental results show that the proposed method detects the motion of vehicles in real-time.

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