• 제목/요약/키워드: Time Invariance

검색결과 71건 처리시간 0.026초

Viewpoint Invariant Person Re-Identification for Global Multi-Object Tracking with Non-Overlapping Cameras

  • Gwak, Jeonghwan;Park, Geunpyo;Jeon, Moongu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권4호
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    • pp.2075-2092
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    • 2017
  • Person re-identification is to match pedestrians observed from non-overlapping camera views. It has important applications in video surveillance such as person retrieval, person tracking, and activity analysis. However, it is a very challenging problem due to illumination, pose and viewpoint variations between non-overlapping camera views. In this work, we propose a viewpoint invariant method for matching pedestrian images using orientation of pedestrian. First, the proposed method divides a pedestrian image into patches and assigns angle to a patch using the orientation of the pedestrian under the assumption that a person body has the cylindrical shape. The difference between angles are then used to compute the similarity between patches. We applied the proposed method to real-time global multi-object tracking across multiple disjoint cameras with non-overlapping field of views. Re-identification algorithm makes global trajectories by connecting local trajectories obtained by different local trackers. The effectiveness of the viewpoint invariant method for person re-identification was validated on the VIPeR dataset. In addition, we demonstrated the effectiveness of the proposed approach for the inter-camera multiple object tracking on the MCT dataset with ground truth data for local tracking.

OA-pSDF BPOF의 특성 및 광학적 구현 (The Characteristics and Optical Implementation of OA-pSDF BPOF)

  • 임종태;박성균;엄주욱;박한규
    • 한국통신학회논문지
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    • 제19권8호
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    • pp.1433-1445
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    • 1994
  • 본 논문에서는 이축 투사 합성 분리함수(OA-pSDF) 근기한 가간섭성 광상관 시스템을 해석하고 이를 광학적으로 구현하고, 사용된 정합필터는 전형적인 pSDF와 단일 기준 평면파를 다중화하여 합성하였다. 합성된 pSDF는 이진위상필터(BPOF)로 변환되어 고가의 공간광변조기 대신 실시간 광상관 시스템에 사용될 수 있도록 컴퓨터 홀로그램(CGH)으로 제작되었다. 특성시험에서 OA-pSDF는 변형불변 특성과 부분집합 영상의 불변에도 좋은 성능을 보임을 알 수 있었다. 시뮬레이션과 광실험에서 제안된 OA-pSDF BPOF는 기존 BPOF의 크기, 회전, 비동일 평면에서의 변위 등에 성능이 저하되는 단점을 극복하고 출력 평면상에서 주어진 위치에서의 상관값을 관측함으로써 클래스간의 분별 또는 동일 클래스로의 인식 등에 훌륭한 분별력을 가짐을 확인할 수 있었다.

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가변구조를 이용한 전기-유압서보계의 위치제어에 관한 연구 (A Study on the Position Control of an Electro-Hydraulic Servomechanism Using Variable Structure System)

  • 허준영;권기수;하석홍;조겸래;이진걸
    • 대한기계학회논문집
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    • 제13권2호
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    • pp.213-220
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    • 1989
  • 본 연구에서는 고정도의 위치제어계를 실현하기 위하여 가변구조제어이론을 전기-유압서보계에 적용하였다.실험은 유압구동부의 공급압력을 변화시켜 유압계의 매개변수를 변화시켜줄 때와 관성하중을 가감하여 부하를 변화시켜 가며 행하였다. 가변구조계에서는 계의 매개변수변동과 부하변동에도 영향을 받지 않음을 종래의 고정구조계와 구조계와 비교, 검토하였다.

비분리 고밀도 이산 웨이브렛 변환을 이용한 디지털 영상처리 (Digital Image Processing Using Non-separable High Density Discrete Wavelet Transformation)

  • 신종홍
    • 디지털산업정보학회논문지
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    • 제9권1호
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    • pp.165-176
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    • 2013
  • This paper introduces the high density discrete wavelet transform using quincunx sampling, which is a discrete wavelet transformation that combines the high density discrete transformation and non-separable processing method, each of which has its own characteristics and advantages. The high density discrete wavelet transformation is one that expands an N point signal to M transform coefficients with M > N. The high density discrete wavelet transformation is a new set of dyadic wavelet transformation with two generators. The construction provides a higher sampling in both time and frequency. This new transform is approximately shift-invariant and has intermediate scales. In two dimensions, this transform outperforms the standard discrete wavelet transformation in terms of shift-invariant. Although the transformation utilizes more wavelets, sampling rates are high costs and some lack a dominant spatial orientation, which prevents them from being able to isolate those directions. A solution to this problem is a non separable method. The quincunx lattice is a non-separable sampling method in image processing. It treats the different directions more homogeneously than the separable two dimensional schemes. Proposed wavelet transformation can generate sub-images of multiple degrees rotated versions. Therefore, This method services good performance in image processing fields.

The Achievable Performance of Unitary-ESPRIT Algorithm for DOA Estimation

  • Satayarak, Peangduen;Rawiwan, Panarat;Supanakoon, Pichaya;Chamchoy, Monchai;Promwong, Sathaporn;Tangtisanon, Prakit
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 ITC-CSCC -3
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    • pp.1578-1581
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    • 2002
  • In this paper, the accuracy of the direction-of-arrival (DOA) estimation of signal impinged on the uniform linear array (ULA) is investigated. The conventional beamformer and Capon’s beamformer categorized in beamformaing techniques as well as MUSIC (MUlti-pie Signal Classification) and ESPRIT (Estimation of Signal Invariance Techniques) categorized in subspace- based methods are employed to estimate the DOAs. From the simulation result under uncorrelated environment, MUSIC can prominently distinguish the DOAs while the beamforming techniques cannot demonstrate the DOAs as clear as MUSIC does. Moreover, Uni-tary ESPRIT is employed to estimate the DOAs under uncorrelated signal conditions. By means of Uni-tary ESPRIT, the estimation has more accuracy with the computational-time reduction. In addition, it incorporates forward-backward averaging; thus Unitary ES-PRIT can overcome the problem of the coherent signal condition.

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3중 밀도 이산 웨이브렛 변환을 이용한 디지털 영상처리 기법 (The Digital Image Processing Method Using Triple-Density Discrete Wavelet Transformation)

  • 신종홍
    • 디지털산업정보학회논문지
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    • 제8권3호
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    • pp.133-145
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    • 2012
  • This paper describes the high density discrete wavelet transformation which is one that expands an N point signal to M transform coefficients with M > N. The double-density discrete wavelet transform is one of the high density discrete wavelet transformation. This transformation employs one scaling function and two distinct wavelets, which are designed to be offset from one another by one half. And it is nearly shift-invariant. Similarly, triple-density discrete wavelet transformation is a new set of dyadic wavelet transformation with two generators. The construction provides a higher sampling in both time and frequency. Specifically, the spectrum of the first wavelet is concentrated halfway between the spectrum of the second wavelet and the spectrum of its dilated version. In addition, the second wavelet is translated by half-integers rather than whole-integers in the frame construction. This arrangement leads to high density wavelet transformation. But this new transform is approximately shift-invariant and has intermediate scales. In two dimensions, this transform outperforms the standard and double-density discrete wavelet transformation in terms of multiple directions. Resultingly, the proposed wavelet transformation services good performance in image and video processing fields.

An Anti-occlusion and Scale Adaptive Kernel Correlation Filter for Visual Object Tracking

  • Huang, Yingping;Ju, Chao;Hu, Xing;Ci, Wenyan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권4호
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    • pp.2094-2112
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    • 2019
  • Focusing on the issue that the conventional Kernel Correlation Filter (KCF) algorithm has poor performance in handling scale change and obscured objects, this paper proposes an anti-occlusion and scale adaptive tracking algorithm in the basis of KCF. The average Peak-to Correlation Energy and the peak value of correlation filtering response are used as the confidence indexes to determine whether the target is obscured. In the case of non-occlusion, we modify the searching scheme of the KCF. Instead of searching for a target with a fixed sample size, we search for the target area with multiple scales and then resize it into the sample size to compare with the learnt model. The scale factor with the maximum filter response is the best target scaling and is updated as the optimal scale for the following tracking. Once occlusion is detected, the model updating and scale updating are stopped. Experiments have been conducted on the OTB benchmark video sequences for compassion with other state-of-the-art tracking methods. The results demonstrate the proposed method can effectively improve the tracking success rate and the accuracy in the cases of scale change and occlusion, and meanwhile ensure a real-time performance.

3차원 모델을 위한 형상 유사성 평가 (Evaluation of shape similarity for 3D models)

  • 김정식;최수미
    • 정보처리학회논문지A
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    • 제10A권4호
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    • pp.357-368
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    • 2003
  • 3차원 모델의 형상 유사성 평가는 의학, 기계 공학, 분자 생물학 등의 많은 분야에서 매우 중요하다. 더욱이 3차원 모델이 웹 상에 보편화됨에 따라 3차원 모델들의 분류와 검색에 관한 연구들이 활발하게 이루어지고 있다. 본 논문에서는 3차원 형상 표현 방법들과 유사성 평가에 대한 주요 개념들을 기술하고, 최근의 형상 비교에 관한 연구들을 다해상도, 위상 기하학, 2차원 영상, 통계학 기반 방법들로 분류하여 그 특징들을 분석하였다. 또한 논문에서 채택한 유일성, 강인성, 불변성, 다해상도, 효율성, 비교범위와 같은 기준을 사용하여 그 성능을 비교 평가하였다. 다해상도 기반 방법은 비교를 위한 계산 시간은 감소시킨 반면 전처리 시간은 증가시켰다. 기하 및 위상 정보를 이용한 방법은 보다 다양한 형태의 모델들을 비교할 수 있었고 부분적인 형상 비교에도 강인하였다. 2차원 영상을 이용한 방법들은 시간 및 공간 복잡도가 높게 나타났다. 통계학 기반 방법들은 포즈 정규화 작업 없이 형상 비교가 가능하였고, 어파인 변환 및 잡음에도 강인한 결과를 보였다.

기하학적 불변벡터 기탄 2D 호모그래피와 비선형 최소화기법을 이용한 카메라 외부인수 측정 (Camera Extrinsic Parameter Estimation using 2D Homography and Nonlinear Minimizing Method based on Geometric Invariance Vector)

  • 차정희
    • 인터넷정보학회논문지
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    • 제6권6호
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    • pp.187-197
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    • 2005
  • 본 논문에서는 불변 점 특징에 기반한 카메라 동작인수 측정방법을 제안한다. 일반적으로 영상의 특징정보는 카메라 뷰포인트에 따라 변하는 단점이 있어 시간이 지나면 정보량이 증가하게 된다. 또한 카메라 외부인수 산출을 위한 비선형 최소제곱 측정을 이용한 LM 방법은 초기값에 따라 최소점에 근접하는 반복회수가 다르고 지역 최소점에 빠질 경우 수렴시간이 증가하는 단점이 있다. 본 논문에서는 이러한 문제를 개선하기 위해 첫째, 기하학의 불변 벡터를 사용하여 특징 모델을 구성하는 것을 제안하였다. 둘째, 2D 호모그래피와 LM 방법을 이용하여 정확도와 수렴도를 향상시키는 2단계 측정 방법을 제안하였다. 실험에서는 제안한 알고리즘의 우수성을 입증하기 위해 기존방법과 제안한 방법을 비교 분석하였다.

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Development of Pose-Invariant Face Recognition System for Mobile Robot Applications

  • Lee, Tai-Gun;Park, Sung-Kee;Kim, Mun-Sang;Park, Mig-Non
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.783-788
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    • 2003
  • In this paper, we present a new approach to detect and recognize human face in the image from vision camera equipped on the mobile robot platform. Due to the mobility of camera platform, obtained facial image is small and pose-various. For this condition, new algorithm should cope with these constraints and can detect and recognize face in nearly real time. In detection step, ‘coarse to fine’ detection strategy is used. Firstly, region boundary including face is roughly located by dual ellipse templates of facial color and on this region, the locations of three main facial features- two eyes and mouth-are estimated. For this, simplified facial feature maps using characteristic chrominance are made out and candidate pixels are segmented as eye or mouth pixels group. These candidate facial features are verified whether the length and orientation of feature pairs are suitable for face geometry. In recognition step, pseudo-convex hull area of gray face image is defined which area includes feature triangle connecting two eyes and mouth. And random lattice line set are composed and laid on this convex hull area, and then 2D appearance of this area is represented. From these procedures, facial information of detected face is obtained and face DB images are similarly processed for each person class. Based on facial information of these areas, distance measure of match of lattice lines is calculated and face image is recognized using this measure as a classifier. This proposed detection and recognition algorithms overcome the constraints of previous approach [15], make real-time face detection and recognition possible, and guarantee the correct recognition irregardless of some pose variation of face. The usefulness at mobile robot application is demonstrated.

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