• Title/Summary/Keyword: global motion compensation`

Search Result 31, Processing Time 0.031 seconds

Progressive Residual Motion Estimation for Constructing Seamless Mosaics (이음매없는 모자이크 구성을 위한 단계적 잔여 움직임 추정)

  • Lee Cheong Woo;Choi Jae Gark;Lee Si-Woong
    • Journal of KIISE:Software and Applications
    • /
    • v.32 no.6
    • /
    • pp.512-522
    • /
    • 2005
  • In this paper an algorithm of image alignments for constructing seamless mosaics is proposed. After the global alignment has been run, there may still be localized mis-registrations present in the mosaic. Due to mis-registrations, there may be seams in the mosaic, such as breaking, blurring, and doubling of lines. To solve this problem, we need an algorithm of residual motion estimation, which minimizes mis-registrations. In the conventional algorithms of residual motion estimation, computational powers are too heavy and estimators of camera parameters are additionally needed such as focal lengths. In the proposed algorithm, residual motion vectors are estimated with the adequate size of estimation and measurement windows and with adjustment of initial vectors according to the established priority. By construction of mosaics with the proposed algorithm, we demonstrate the removal of seams by mis-registrations.

Recursive compensation algorithm application to the optimal edge selection

  • Chung, C.H.;Lee, K.S.
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 1992.10b
    • /
    • pp.79-84
    • /
    • 1992
  • Path planning is an important task for optimal motion of a robot in structured or unstructured environment. The goal of this paper is to plan the optimal collision-free path in 3D, when a robot is navigated to pick up some tools or to repair some parts from various locations. To accomplish the goal, the Path Coordinator is proposed to have the capabilities of an obstacle avoidance strategy and a traveling salesman problem strategy (TSP). The obstacle avoidance strategy is to plan the shortest collision-free path between each pair of n locations in 2D or in 3D. The TSP strategy is to compute a minimal system cost of a tour that is defined as a closed path navigating each location exactly once. The TSP strategy can be implemented by the Hopfield Network. The obstacle avoidance strategy in 2D can be implemented by the VGraph Algorithm. However, the VGraph Algorithm is not useful in 3D, because it can't compute the global optimality in 3D. Thus, the Path Coordinator is used to solve this problem, having the capabilities of selecting the optimal edges by the modified Genetic Algorithm and computing the optimal nodes along the optimal edges by the Recursive Compensation Algorithm.

  • PDF

Surf points based Moving Target Detection and Long-term Tracking in Aerial Videos

  • Zhu, Juan-juan;Sun, Wei;Guo, Bao-long;Li, Cheng
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.10 no.11
    • /
    • pp.5624-5638
    • /
    • 2016
  • A novel method based on Surf points is proposed to detect and lock-track single ground target in aerial videos. Videos captured by moving cameras contain complex motions, which bring difficulty in moving object detection. Our approach contains three parts: moving target template detection, search area estimation and target tracking. Global motion estimation and compensation are first made by grids-sampling Surf points selecting and matching. And then, the single ground target is detected by joint spatial-temporal information processing. The temporal process is made by calculating difference between compensated reference and current image and the spatial process is implementing morphological operations and adaptive binarization. The second part improves KALMAN filter with surf points scale information to predict target position and search area adaptively. Lastly, the local Surf points of target template are matched in this search region to realize target tracking. The long-term tracking is updated following target scaling, occlusion and large deformation. Experimental results show that the algorithm can correctly detect small moving target in dynamic scenes with complex motions. It is robust to vehicle dithering and target scale changing, rotation, especially partial occlusion or temporal complete occlusion. Comparing with traditional algorithms, our method enables real time operation, processing $520{\times}390$ frames at around 15fps.

Real-Time Object Detection System Based on Background Modeling in Infrared Images (적외선영상에서 배경모델링 기반의 실시간 객체 탐지 시스템)

  • Park, Chang-Han;Lee, Jae-Ik
    • Journal of the Institute of Electronics Engineers of Korea CI
    • /
    • v.46 no.4
    • /
    • pp.102-110
    • /
    • 2009
  • In this paper, we propose an object detection method for real-time in infrared (IR) images and PowerPC (PPC) and H/W design based on field programmable gate array (FPGA). An open H/W architecture has the advantages, such as easy transplantation of HW and S/W, support of compatibility and scalability for specification of current and previous versions, common module design using standardized design, and convenience of management and maintenance. Proposed background modeling for an open H/W architecture design decreases size of search area to construct a sparse block template of search area in IR images. We also apply to compensate for motion compensation when image moves in previous and current frames of IR sensor. Separation method of background and objects apply to adaptive values through time analysis of pixel intensity. Method of clutter reduction to appear near separated objects applies to median filter. Methods of background modeling, object detection, median filter, labeling, merge in the design embedded system execute in PFC processor. Based on experimental results, proposed method showed real-time object detection through global motion compensation and background modeling in the proposed embedded system.

Investigation of Sensor Models for Precise Geolocation of GOES-9 Images

  • Hur Dongseok;Lee Tae-Yoon;Kim Taejung
    • Proceedings of the KSRS Conference
    • /
    • 2005.10a
    • /
    • pp.91-94
    • /
    • 2005
  • A numerical formula that presents relationship between a point of a satellite image and its ground position is called a sensor model. For precise geolocation of satellite images, we need an error-free sensor model. However, the sensor model based on GOES ephemeris data has some error, in particular after Image Motion Compensation (IMC) mechanism has been turned off. To solve this problem, we investigate three sensor models: Collinearity model, Direct Linear Transform (DLT) model and Orbit-based model. We apply matching between GOES images and global coastline database and use successful results as control points. With control points we improve the initial image geolocation accuracy using the three models. We compare results from three sensor models that are applied to GOES-9 images. As a result, a suitable sensor model for precise geolocation of GOES-9 images is proposed.

  • PDF

A Systolic Array for High-Speed Computing of Full Search Block Matching Algorithm

  • Jung, Soon-Ho;Woo, Chong-Ho
    • Journal of Korea Multimedia Society
    • /
    • v.14 no.10
    • /
    • pp.1275-1286
    • /
    • 2011
  • This paper proposes a high speed systolic array architecture for full search block matching algorithm (FBMA). The pixels of the search area for a reference block are input only one time to find the matched candidate block and reused to compute the sum of absolute difference (SAD) for the adjacent candidate blocks. Each row of designed 2-dimensional systolic array compares the reference block with the adjacent blocks of the same row in search area. The lower rows of the designed array get the pixels from the upper row and compute the SAD with reusing the overlapped pixels of the candidate blocks within same column of the search area. This designed array has no data broadcasting and global paths. The comparison with existing architectures shows that this array is superior in terms of throughput through it requires a little more hardware.

Tracking and Interpretation of Moving Object in MPEG-2 Compressed Domain (MPEG-2 압축 영역에서 움직이는 객체의 추적 및 해석)

  • Mun, Su-Jeong;Ryu, Woon-Young;Kim, Joon-Cheol;Lee, Joon-Hoan
    • The KIPS Transactions:PartB
    • /
    • v.11B no.1
    • /
    • pp.27-34
    • /
    • 2004
  • This paper proposes a method to trace and interpret a moving object based on the information which can be directly obtained from MPEG-2 compressed video stream without decoding process. In the proposed method, the motion flow is constructed from the motion vectors included in compressed video. We calculate the amount of pan, tilt, and zoom associated with camera operations using generalized Hough transform. The local object motion can be extracted from the motion flow after the compensation with the parameters related to the global camera motion. Initially, a moving object to be traced is designated by user via bounding box. After then automatic tracking Is performed based on the accumulated motion flows according to the area contributions. Also, in order to reduce the cumulative tracking error, the object area is reshaped in the first I-frame of a GOP by matching the DCT coefficients. The proposed method can improve the computation speed because the information can be directly obtained from the MPEG-2 compressed video, but the object boundary is limited by macro-blocks rather than pixels. Also, the proposed method is proper for approximate object tracking rather than accurate tracing of an object because of limited information available in the compressed video data.

Observation Likelihood Function Design and Slippage Error Compensation Scheme for Indoor Mobile Robots (실내용 이동로봇을 위한 위치추정 관측모델 설계 및 미끄러짐 오차 보상 기법 개발)

  • Moon, Chang-Bae;Kim, Kyoung-Rok;Song, Jae-Bok;Chung, Woo-Jin
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.13 no.11
    • /
    • pp.1092-1098
    • /
    • 2007
  • A mobile robot localization problem can be classified into following three sub-problems as an observation likelihood model, a motion model and a filtering technique. So far, we have developed the range sensor based, integrated localization scheme, which can be used in human-coexisting real environment such as a science museum and office buildings. From those experiences, we found out that there are several significant issues to be solved. In this paper, we focus on three key issues, and then illustrate our solutions to the presented problems. Three issues are listed as follows: (1) Investigation of design requirements of a desirable observation likelihood model, and performance analysis of our design (2) Performance evaluation of the localization result by computing the matching error (3) The semi-global localization scheme to deal with localization failure due to abrupt wheel slippage In this paper, we show the significance of each concept, developed solutions and the experimental results. Experiments were carried out in a typical modern building environment, and the results clearly show that the proposed solutions are useful to develop practical and integrated localization schemes.

Path coordinator by the modified genetic algorithm

  • Chung, C.H.;Lee, K.S.
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 1991.10b
    • /
    • pp.1939-1943
    • /
    • 1991
  • Path planning is an important task for optimal motion of a robot in structured or unstructured environment. The goal of this paper is to plan the shortest collision-free path in 3D, when a robot is navigated to pick up some tools or to repair some parts from various locations. To accomplish the goal of this paper, the Path Coordinator is proposed to have the capabilities of an obstacle avoidance strategy[3] and a traveling salesman problem strategy(TSP)[23]. The obstacle avoidance strategy is to plan the shortest collision-free path between each pair of n locations in 2D or in 3D. The TSP strategy is to compute a minimal system cost of a tour that is defined as a closed path navigating each location exactly once. The TSP strategy can be implemented by the Neural Network. The obstacle avoidance strategy in 2D can be implemented by the VGraph Algorithm. However, the VGraph Algorithm is not useful in 3D, because it can't compute the global optimality in 3D. Thus, the Path Coordinator is proposed to solve this problem, having the capabilities of selecting the optimal edges by the modified Genetic Algorithm[21] and computing the optimal nodes along the optimal edges by the Recursive Compensation Algorithm[5].

  • PDF

Fast ST-MRF based tracking using ROI-based GMC (관심영역 기반 전역 움직임 보상을 이용한 ST-MRF 기반 추적기 고속화 방법)

  • Park, Dong-Min;Lee, Dong-Kyu;Kim, Sang-Min;Oh, Seoung-Jun
    • Proceedings of the Korean Society of Broadcast Engineers Conference
    • /
    • 2014.11a
    • /
    • pp.142-145
    • /
    • 2014
  • 동영상에서의 객체 추적 알고리즘에 대한 활발한 연구가 진행되고 있음에도 불구하고 실시간 객체추적을 위해서는 여전히 정확도, 복잡도 등에서의 성능향상이 필요하다. 압축영역 기반 방식에서는 전역 움직임 보상(GMC : Global Motion Compensation)과정을 거쳐 추적하려는 객체와 배경을 구분한다. 전역 움직임 보상방법은 프레임 전 영역을 대상으로 하는 연산으로 전체 추적 시스템에서 차지하는 복잡도가 높다. 본 논문은 관심영역(ROI : Region Of Interest) 기반 전역 움직임 보상방법을 이용한 ST-MRF(Spatio-Temporal Markov Random Field)기반 추적기 고속화 방법을 제안한다. 관심영역을 기반으로 전역 움직임 보상을 적용함으로써 객체와 배경을 분리할 뿐만 아니라 알고리즘의 복잡도를 효과적으로 줄일 수 있다. 제안하는 방법의 추적성능은 평균 precision 87.29%, recall 82.58%, F-measure 83.78%로 기존방법과 비교하여 약 1%의 차이를 유지하였으며 전체 시스템의 수행시간은 평균 29.95ms로 기존방법과 비교하여 1.74배의 속도향상을 보였다.

  • PDF