• Title/Summary/Keyword: motion-image

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A Distance Estimation Method of Object′s Motion by Tracking Field Features and A Quantitative Evaluation of The Estimation Accuracy (배경의 특징 추적을 이용한 물체의 이동 거리 추정 및 정확도 평가)

  • 이종현;남시욱;이재철;김재희
    • Proceedings of the IEEK Conference
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    • 1999.11a
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    • pp.621-624
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    • 1999
  • This paper describes a distance estimation method of object's motion in soccer image sequence by tracking field features. And we quantitatively evaluate the estimation accuracy We suppose that the input image sequence is taken with a camera on static axis and includes only zooming and panning transformation between frames. Adaptive template matching is adopted for non-rigid object tracking. For background compensation, feature templates selected from reference frame image are matched in following frames and the matched feature point pairs are used in computing Affine motion parameters. A perspective displacement field model is used for estimating the real distance between two position on Input Image. To quantitatively evaluate the accuracy of the estimation, we synthesized a 3 dimensional virtual stadium with graphic tools and experimented on the synthesized 2 dimensional image sequences. The experiment shows that the average of the error between the actual moving distance and the estimated distance is 1.84%.

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Enhancement of noisy image sequence using order statistic-adaptive weighted average hybrid filters (순서 통계형-적응 가중평균 혼성필터를 이용한 잡음화된 영상열의 향상)

  • 박순영
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.1
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    • pp.193-204
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    • 1997
  • In this research we propose the design of the Order Statistic-Adaptive Weighted Average Hybrid(OS-AWAH) filter which can suppress noise from the corrupted image sequence effectively while preserving the image structure. The proposed filter combines the desirable properties of the order static based spatial filter which can preserve the image structure while reducing noise and the adaptive weighted average based temporal filter which can adapt the filtering weights according to the amount of motion without motion estimation. Performance characteristics of the OS-AWAH filter in noisy sequences containing moving step edges are investigated throuth computer simulations and compared with the median based filters such as 3-D WM(weighted median) filter, MMF (multistage median filter), ADCWM(adaptive directional center weighted median) filter. The visual evaluations are also carried out by applyin gthe filters to the real images. The statistical analysis and experimental reslts show that the OS-AWAH filter is effective in preserving image structures while suppressing noise effectively without motion compensation preprocessing.

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An Image Segmentation Technique For Very Low Bit Rate Video Coding

  • Jung, Seok-Yoon;Kim, Rin-Chul;Lee, Sang-Uk
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 1997.06a
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    • pp.19-24
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    • 1997
  • This paper describes an image segmentation technique for the object-oriented coding at very low bit rates. By noting that, in the object-oriented coding technique, each objects are represented by 3 parameters, namely, shape, motion, and color informations, we propose a segmentation technique, in which the 3 parameters are fully exploited. To achieve this goal, starting with the color space conversion and the noise reduction, the input image is divided into many small regions by the K-menas algorithm on the O-K-S color space. Then, each regions are merged, according to the shape and motion information. In simultations, it is shown that the proposed technique segments the input image into relevant objects, according to the shape and motion as well as the colors. In addition, in order to evaluate the performance of the proposed technique, we introduce the notion of the interesting regions, and provide the results of encoding the image with emphasizing the interesting regions.

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FEASIBILITY ON GENERATING STEREO MOSAIC IMAGE

  • Noh, Myoung-Jong;Lee, Sung-Hun;Cho, Woo-Sug
    • Proceedings of the KSRS Conference
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    • 2005.10a
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    • pp.201-204
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    • 2005
  • Recently, the generation of panoramic images and high quality mosaic images from video sequences has been attempted by a variety of investigations. Among a matter of investigation, in this paper, left and right stereo mosaic image generation utilizing airborne-video sequence images is focused upon. The stereo mosaic image is generated by creating left and right mosaic image which is generated by front and rear slit having different viewing angle in consecutive video frame images. The generation of stereo mosaic image proposed in this paper consists of several processes: camera parameter estimation for each video frame image, rectification, slicing, motion parallax elimination and image mosaicking. However it is necessary to check the feasibility on generating stereo mosaic image as explained processes. Therefore, in this paper, we performed the feasibility test on generating stereo mosaic image using video frame images. In doing so, anaglyphic image for stereo mosaic images is generated and tested for feasibility check.

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Multiple Pedestrians Detection using Motion Information and Support Vector Machine from a Moving Camera Image (이동 카메라 영상에서 움직임 정보와 Support Vector Machine을 이용한 다수 보행자 검출)

  • Lim, Jong-Seok;Park, Hyo-Jin;Kim, Wook-Hyun
    • Journal of the Institute of Convergence Signal Processing
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    • v.12 no.4
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    • pp.250-257
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    • 2011
  • In this paper, we proposed the method detecting multiple pedestrians using motion information and SVM(Support Vector Machine) from a moving camera image. First, we detect moving pedestrians from both the difference image and the projection histogram which is compensated for the camera ego-motion using corresponding feature sets. The difference image is simple method but it is not detected motionless pedestrians. Thus, to fix up this problem, we detect motionless pedestrians using SVM The SVM works well particularly in binary classification problem such as pedestrian detection. However, it is not detected in case that the pedestrians are adjacent or they move arms and legs excessively in the image. Therefore, in this paper, we proposed the method detecting motionless and adjacent pedestrians as well as people who take excessive action in the image using motion information and SVM The experimental results on our various test video sequences demonstrated the high efficiency of our approach as it had shown an average detection ratio of 94% and False Positive of 2.8%.

Improvement of Radar Images Using Time-Frequency Transform (시간-주파수 영역 해석법을 이용한 레이더 영상 품질 개선에 대한 연구)

  • Jung, Sang-Won;Kim, Kyung-Tae
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.21 no.1
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    • pp.14-19
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    • 2010
  • In this paper, an efficient algorithm is developed to perform target rotational motion compensation to achieve the clear inverse synthetic aperture radar(ISAR) image. The algorithm is based on a time-frequency technique. This algorithm provides an efficient method to resolve the blurring image caused by the time-varying behavior of the target scattering centers and leads to a well-focused ISAR image. Results demonstrate that the time-frequency techniques can improve the blurring ISAR image when an aircraft is in complex motion, such as maneuvering, rotation and acceleration.

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.

Gait Recognition using Modified Motion Silhouette Image (개선된 움직임 실루엣 영상을 이용한 발걸음 인식에 관한 연구)

  • Hong Sung-Jun;Lee Hee-Sung;Oh Kyong-Sae;Kim Eun-Tai
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.3
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    • pp.266-270
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    • 2006
  • In this paper, we propose the human identification system based on Hidden Markov model using gait. Since each gait cycle consists of a set of continuous motion states and transition across states has probabilistic dependences, individual gait can be modeled using Hidden Markov model. We assume that individual gait consists of N discrete transitions and we propose gait feature representation, Modified Motion Silhouette Image (MMSI) to represent and recognize individual gait. MMSI is defined as a gray-level image and it provides not only spatial information but also temporal information. The experimental results show gait recognition performance of proposed system.

Estimation of Moving Direction of Objects for Vehicle Tracking in Underground Parking Lot (지하 주차장 차량 추적을 위한 객체의 이동 방향 추정)

  • Nguyen, Huu Thang;Kim, Jaemin
    • Journal of Korea Multimedia Society
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    • v.24 no.2
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    • pp.305-311
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    • 2021
  • One of the highly reliable object tracking methods is to trace objects by associating objects detected by deep learning. The detected object is represented by a rectangular box. The box has information such as location and size. Since the tracker has motion information of the object in addition to the location and size, knowing additional information about the motion of the detected box can increase the reliability of object tracking. In this paper, we present a new method of reliably estimating the moving direction of the detected object in underground parking lot. First, the frame difference image is binarized for detecting motion energy, change due to the object motion. Then, a cumulative binary image is generated that shows how the motion energy changes over time. Next, the moving direction of the detected box is estimated from the accumulated image. We use a new cost function to accurately estimate the direction of movement of the detected box. The proposed method proves its performance through comparative experiments of the existing methods.

Motion and Image Matching Algorithms and Implementation for Motion Synchronization in a Vehicle Driving Simulator (차량 운전 시뮬레이터에서 모션과 영상의 동기화를 위한 알고리즘 및 구현 방안)

  • Kim, Hun-Se;Kim, Dae-Seop;Kim, Dong Hwan
    • The Journal of Korea Robotics Society
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    • v.12 no.2
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    • pp.184-193
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    • 2017
  • This work shows how to create an algorithm and implementation for motion and image matching between a vehicle simulator and Unity 3D based virtual object. The motion information of the virtual vehicle is transmitted to the real simulator via a RS232 communication protocol, and the motion is controlled based on the inverse kinematics solution of the platform adopting rotary-type six actuators driving system. Wash-out filters to implement the effective motion of the motion platform are adopted, and thereby reduce the dizziness and increase the realistic sense of motion. Furthermore, the simulator system is successfully designed aiming to reducing size and cost with adaptation of rotary-type six actuators, real driving environment via VR (Virtual Reality), and control schemes which employ a synchronization between 6 motors and 3rd order motion profiles. By providing relatively big sense of motion particularly in impact and straight motions mainly causing simulator sickness, dizziness is remarkably reduced, thereby enhancing the sense of realistic motion.