• Title/Summary/Keyword: Dynamic Scene

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Gamma Correction for Local Brightness and Detail Enhancement of HDR Images (HDR 영상의 지역적 밝기 및 디테일 향상을 위한 감마 보정 기법)

  • Lee, Seung-Yun;Ha, Ho-Gun;Song, Kun-Woen;Ha, Yeong-Ho
    • Journal of Korea Multimedia Society
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    • v.19 no.5
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    • pp.837-847
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    • 2016
  • Tone mapping for High Dynamic Range(HDR) image provides matching human visual perception between real world scene and displayable devices. Recently, a tone mapping algorithm based on localized gamma correction is proposed. This algorithm is using human visual properties of contrast and colorfulness with background intensity, generating a weight map for gamma correction. However, this method have limitations of controlling enhancement region as well as generating halo artifacts caused by the weight map construction. To overcome aforementioned limitations, proposed algorithm in this paper modifies previous weight map, considering base layer intensity of input luminance channel. By determining enhancement region locally and globally based on base layer intensity, gamma values are corrected accordingly. Therefore, proposed algorithm selectively enhances local brightness and controls strength of edges. Subjective evaluation using z-score shows that our proposed algorithm outperforms the conventional methods.

Robust background acquisition and moving object detection from dynamic scene caused by a moving camera (움직이는 카메라에 의한 변화하는 환경하의 강인한 배경 획득 및 유동체 검출)

  • Kim, Tae-Ho;Jo, Kang-Hyun
    • Proceedings of the Korean Information Science Society Conference
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    • 2007.06c
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    • pp.477-481
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    • 2007
  • A background is a part where do not vary too much or frequently change in an image sequence. Using this assumption, it is presented a background acquisition algorithm for not only static but also dynamic view in this paper. For generating background, we detect a region, where has high correlation rate compared within selected region in the prior pyramid image, from the searching region in the current image. Between a detected region in the current image and a selected region in the prior image, we calculate movement vector for each regions in time sequence. After we calculate whole movement vectors for two successive images, vector histogram is used to determine the camera movement. The vector which has the highest density in the histogram is determined a camera movement. Using determined camera movement, we classify clusters based on pixel intensities which pixels are matched with prior pixels following camera movement. Finally we eliminate clusters which have lower weight than threshold, and combine remained clusters for each pixel to generate multiple background clusters. Experimental results show that we can automatically detect background whether camera move or not.

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A Lane Departure Warning Algorithm Based on an Edge Distribution Function (에지분포함수 기반의 차선이탈경보 알고리즘)

  • 이준웅;이성웅
    • Transactions of the Korean Society of Automotive Engineers
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    • v.9 no.3
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    • pp.143-154
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    • 2001
  • An algorithm for estimating the lane departure of a vehicle is derived and implemented based on an EDF(edge distribution function) obtained from gray-level images taken by a CCD camera mounted on a vehicle. As the function of edge direction, the EDF is aimed to show the distribution of edge direction and to estimate the possibility of lane departure with respect to its symmetric axis and local mamma. The EDF plays important roles: 1) It reduces noisy effects caused by dynamic road scene. 2) It makes possible lane identification without camera modeling. 3) It also leads LDW(lane departure warning) problem to a mathematical approach. When the situations of lane departure such that the vehicle approaches to lane marks or runs in the vicinity of the lane marks are occurred, the orientation of lane marks in images is changed, and then the situations are immediately reflected to the EDF. Accordingly, the lane departure is estimated by studying the shape of the EDF. The proposed EDF-based algorithm enhanced the adaptability to cope with the random and dynamic road environments, and eventually led to the reliable LDW system.

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High Speed Self-Adaptive Algorithms for Implementation in a 3-D Vision Sensor (3-D 비젼센서를 위한 고속 자동선택 알고리즘)

  • Miche, Pierre;Bensrhair, Abdelaziz;Lee, Sang-Goog
    • Journal of Sensor Science and Technology
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    • v.6 no.2
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    • pp.123-130
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    • 1997
  • In this paper, we present an original stereo vision system which comprises two process: 1. An image segmentation algorithm based on new concept called declivity and using automatic thresholds. 2. A new stereo matching algorithm based on an optimal path search. This path is obtained by dynamic programming method which uses the threshold values calculated during the segmentation process. At present, a complete depth map of indoor scene only needs about 3 s on a Sun workstation IPX, and this time will be reduced to a few tenth of second on a specialised architecture based on several DSPs which is currently under consideration.

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Robust Features and Accurate Inliers Detection Framework: Application to Stereo Ego-motion Estimation

  • MIN, Haigen;ZHAO, Xiangmo;XU, Zhigang;ZHANG, Licheng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.1
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    • pp.302-320
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    • 2017
  • In this paper, an innovative robust feature detection and matching strategy for visual odometry based on stereo image sequence is proposed. First, a sparse multiscale 2D local invariant feature detection and description algorithm AKAZE is adopted to extract the interest points. A robust feature matching strategy is introduced to match AKAZE descriptors. In order to remove the outliers which are mismatched features or on dynamic objects, an improved random sample consensus outlier rejection scheme is presented. Thus the proposed method can be applied to dynamic environment. Then, geometric constraints are incorporated into the motion estimation without time-consuming 3-dimensional scene reconstruction. Last, an iterated sigma point Kalman Filter is adopted to refine the motion results. The presented ego-motion scheme is applied to benchmark datasets and compared with state-of-the-art approaches with data captured on campus in a considerably cluttered environment, where the superiorities are proved.

Visual Sensing of Fires Using Color and Dynamic Features (컬러와 동적 특징을 이용한 화재의 시각적 감지)

  • Do, Yong-Tae
    • Journal of Sensor Science and Technology
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    • v.21 no.3
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    • pp.211-216
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    • 2012
  • Fires are the most common disaster and early fire detection is of great importance to minimize the consequent damage. Simple sensors including smoke detectors are widely used for the purpose but they are able to sense fires only at close proximity. Recently, due to the rapid advances of relevant technologies, vision-based fire sensing has attracted growing attention. In this paper, a novel visual sensing technique to automatically detect fire is presented. The proposed technique consists of multiple steps of image processing: pixel-level, block-level, and frame level. At the first step, fire flame pixel candidates are selected based on their color values in YIQ space from the image of a camera which is installed as a vision sensor at a fire scene. At the second step, the dynamic parts of flames are extracted by comparing two consecutive images. These parts are then represented in regularly divided image blocks to reduce pixel-level detection error and simplify following processing. Finally, the temporal change of the detected blocks is analyzed to confirm the spread of fire. The proposed technique was tested using real fire images and it worked quite reliably.

Fast image stitching method for handling dynamic object problems in Panoramic Images

  • Abdukholikov, Murodjon;Whangbo, Taegkeun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.11 no.11
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    • pp.5419-5435
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    • 2017
  • The construction of panoramic images on smartphones and low-powered devices is a challenging task. In this paper, we propose a new approach for smoothly stitching images on mobile phones in the presence of moving objects in the scene. Our main contributions include handling moving object problems, reducing processing time, and generating rectangular panoramic images. First, unique and robust feature points are extracted using fast ORB method and a feature matching technique is applied to match the extracted feature points. After obtaining good matched feature points, we employ the non-deterministic RANSAC algorithm to discard wrong matches, and the hommography transformation matrix parameters are estimated with the algorithm. Afterward, we determine precise overlap regions of neighboring images and calculate their absolute differences. Then, thresholding operation and noise removal filtering are applied to create a mask of possible moving object regions. Sequentially, an optimal seam is estimated using dynamic programming algorithm, and a combination of linear blending with the mask information is applied to avoid seam transition and ghosting artifacts. Finally, image-cropping operation is utilized to obtain a rectangular boundary image from the stitched image. Experiments demonstrate that our method is able to produce panoramic images quickly despite the existence of moving objects.

A Study on the Motion Object Detection Method for Autonomous Driving (자율주행을 위한 동적 객체 인식 방법에 관한 연구)

  • Park, Seung-Jun;Park, Sang-Bae;Kim, Jung-Ha
    • Journal of the Korean Society of Industry Convergence
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    • v.24 no.5
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    • pp.547-553
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    • 2021
  • Dynamic object recognition is an important task for autonomous vehicles. Since dynamic objects exhibit a higher collision risk than static objects, our own trajectories should be planned to match the future state of moving elements in the scene. Time information such as optical flow can be used to recognize movement. Existing optical flow calculations are based only on camera sensors and are prone to misunderstanding in low light conditions. In this regard, to improve recognition performance in low-light environments, we applied a normalization filter and a correction function for Gamma Value to the input images. The low light quality improvement algorithm can be applied to confirm the more accurate detection of Object's Bounding Box for the vehicle. It was confirmed that there is an important in object recognition through image prepocessing and deep learning using YOLO.

Analysis of Roles of Lighting and Background Musik for Storytelling - a Case Study of Disney's Short Animated Film (스토리텔링에서의 조명과 배경음악의 역할 분석 -디즈니 단편 애니메이션 <페이퍼맨>을 중심으로)

  • Park, Eun-Hea
    • Journal of Korea Multimedia Society
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    • v.18 no.8
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    • pp.988-995
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    • 2015
  • In 2013, Academy Award for Best Animated Short Film was granted to Walt Disney's short animation, (2012). With various aspects of its excellence, I focus on the very effective use of digital lightings and underscores for storytelling as its success factors. In this respect, this paper aims at analyzing the roles of the visual factors, especially tone, contrast, etc. created by lightings, and audio factors, especially underscores, in the film's story development. I find that can be characterized by the well-built story structure with distinct three acts. The main stream of the story is expressed with the overall mood that is created by the fine adjustments of brightness of the main light, and contrast. And the direction and the intensity of the lighting successfully describe the emotions of the characters in each scene. In addition, I find that properly chosen and positioned underscores make the development of the story more dynamic and more harmonized.

A New Vertex Coding Scheme Using The Center of the Gravity of a Triangle (삼각형의 무게 중심을 이용한 새로운 다각 근사화 장점 부호화 기법)

  • 윤병주;강현수;조순제;김성대
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.24 no.6B
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    • pp.1174-1182
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    • 1999
  • Recently the shape information of the visual object in the scene is more important, as the completion of the MPEG-4 standard and the progress of the MPEG-7 standard. This paper represents the study of effective coding method of vertices that are used in the polygonal approximation to represent the feature of visual object. In the proposed method, we make the centers of gravity of triangles that are made using the vertices of polygonal approximation and encode them sequentially We can get a coding gain because the centers of the gravity of triangles have narrower dynamic ranges.

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