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检索条件"机构=Image Processing and Intelligent System Laboratory Graduate School of Advanced Imaging Science"

共 81 条记录，以下是21-30 订阅

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Peripheral region enhancement of geometrically compensated images from a fisheye lens

Peripheral region enhancement of geometrically compensated i...

引用

1st IEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2011

作者： Kim, Donggyun Kim, Seonyung Paik, Joonki Jung, Junghoon Kim, Taechan Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea Republic of System LSI Samsung Electronics Co. Ltd. Suwon Korea Republic of

ISBN: (纸本)9781457702341

In this paper, we propose a peripheral region enhancement method for geometrically compensated images from a fisheye lens. The proposed method provides a novel filtering method based on the degradation model of a fisheye lens. More specifically, we first present a space-variant image degradation model using generic Gaussian function with geometric distortion. We then apply the truncated constraint least squares (TCLS) filter for restoring the peripheral region of the image in the real-time, space-adaptive manner. Experimental results demonstrate that the proposed method can enhance the peripheral region while keeping the high-quality center region. © 2011 IEEE.

关键词： image enhancement

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Active shape model-based gait recognition using infrared images

Active shape model-based gait recognition using infrared ima...

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作者： Kim, Daehee Lee, Seungwon Paik, Joonki Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University 221 Heuksuk-Dong Dongjak-Ku Seoul 156-756 Korea Republic of

ISBN: (纸本)9783642105456

We present a gait recognition system using infra-red (IR) images. Since an IR camera is not affected by the intensity of illumination, it is able to provide constant recognition performance regardless of the amount of illumination. Model-based object tracking algorithms enable robust tracking with partial occlusions or dynamic illumination. However, this algorithm often fails in tracking objects if strong edge exists near the object. Replacement of the input image by an IR image guarantees robust object region extraction because background edges do not affect the IR image. In conclusion, the proposed gait recognition algorithm improves accuracy in object extraction by using IR images and the improvements finally increase the recognition rate of gaits. © 2009 Springer-Verlag Berlin Heidelberg.

关键词： image enhancement

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Efficient Pavement Crack Detection in Drone images using Deep Neural Networks

Efficient Pavement Crack Detection in Drone Images using Dee...

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International Conference on Electronics, Information and Communications (ICEIC)

作者： Heegwang Kim Junghoon Sung Mingi Kim Chanyeong Park Joonki Paik Image Processing and Intelligent System Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea Image Processing and Intelligent System Laboratory Graduate School of Artificial Intelligence Chung-Ang University Seoul Korea

Since the drone input images are usually filmed at very high altitudes and with various viewing angles, cracks appear in many different sizes and shapes. A commonly used crack detection dataset has a small size such as 480x320, and it is important that how well it detects the prominent continuous cracks. To detect pavement cracks, we proposed an efficient crack detection network. The proposed network achieved better performance than the conventional network.

关键词： Deep learning Shape Neural networks Drones

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Multi-frame example-based super-resolution using locally directional self-similarity

Multi-frame example-based super-resolution using locally dir...

引用

IEEE International Conference on Consumer Electronics (ICCE)

作者： Seokhwa Jeong Inhye Yoon Jaehwan Jeon Joonki Paik Image Processing and Intelligent System Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea

ISBN: (纸本)9781479975440

This paper presents a multi-frame example-based super-resolution (SR) algorithm using locally directional self-similarity. Existing example-based super-resolution algorithms generate patches using multiple training images or single self-image. On the other hand the proposed method minimizes the patch mismatching error by generating a patch dictionary in a local region of multiple, adjacent frames. As a result, the proposed algorithm can remove interpolation artifacts based on a degradation model of low-resolution images. The dictionary is classified by the orientation of patches for fast searching. The proposed algorithm consists of two steps: i) dictionary generation based on the image degradation model and ii) multi-frame image reconstruction for super-resolution. Experimental results show that the proposed SR algorithm provides better reconstructed images with less undesired artifacts than existing methods.

关键词： image resolution Dictionaries Interpolation Degradation image reconstruction Classification algorithms Consumer electronics

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Fisheye lens-based surveillance camera for wide field-of-view monitoring

Fisheye lens-based surveillance camera for wide field-of-vie...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Hyungtae Kim Eunjung Chae Gwanghyun Jo Joonki Paik Image Processing and Intelligent System Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea

ISBN: (纸本)9781479975440

This paper presents a single fisheye lens camera-based visual surveillance system for monitoring a wide area. A fisheye lens has a wider field-of-view (FOV) than normal lenses at the cost of a barrel distortion in the acquired image. After correcting the barrel distortion, the proposed algorithm detects objects, and performs tracking using a histogram-based Gaussian mixture model (GMM). Experimental results show that the proposed algorithm can efficiently detect objects by reducing the geometric distortion of the input image. For this reason it is suitable for not only surveillance cameras but also consumer applications of video object detection and recognition.

关键词： Lenses Cameras Surveillance Histograms Object detection Visualization

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Optical flow-based tracking of deformable objects using a non-prior training active feature model 5th

Optical flow-based tracking of deformable objects using a no...

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5th Pacific Rim Conference on Multimedia, PCM 2004

作者： Kim, Sangjin Kang, Jinyoung Shin, Jeongho Lee, Seongwon Paik, Joonki Kang, Sangkyu Abidi, Besma Abidi, Mongi Image Processing and Intelligent Systems Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University 221 Huksuk-Dong Tongjak-Ku Seoul156-756 Korea Republic of Imaging Robotics and Intelligent Systems Laboratory Department of Electrical and Computer Engineering The University of Tennessee KnoxvilleTN37996-2100 United States

ISBN: (纸本)9783540239857

This paper presents a feature point tracking algorithm using optical flow under the non-prior training active feature model (NPT-AFM) framework. The proposed algorithm mainly focuses on analysis of deformable objects, and provides real-time, robust tracking. The proposed object tracking procedure can be divided into two steps: (i) optical flow-based tracking of feature points and (ii) NPT-AFM for robust tracking. In order to handle occlusion problems in object tracking, feature points inside an object are estimated instead of its shape boundary of the conventional active contour model (ACM) or active shape model (ASM), and are updated as an element of the training set for the AFM. The proposed NPT-AFM framework enables the tracking of occluded objects in complicated background. Experimental results show that the proposed NPT-AFM-based algorithm can track deformable objects in real-time. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Optical flows

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Robust feature detection using particle keypoints and its application to video stabilization in a consumer handheld camera

Robust feature detection using particle keypoints and its ap...

引用

IEEE International Conference on Consumer Electronics, ICCE 2016

作者： Jeon, Semi Yoon, Inhye Yang, Seung'I Kim, Bongmo Kim, Jisung Paik, Joonki Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea Republic of Video Technology Lab. Future Technology RandD Division SK Telecom Korea Republic of

ISBN: (纸本)9781467383646

Compact, portable digital cameras have been popular to consumers. This paper presents a robust feature detection method using particle keypoints and its application to video stabilization. The proposed video stabilization algorithm consists of three steps: i) generation of a flat region map based on the Gaussian filter, ii) robust feature point detection using particle keypoints, and iii) camera paths estimation for enhancing a shaky video. As a result, the proposed algorithm can estimate optimal homography by redefining important feature points using particle keypoints in the flat region map. The proposed robust feature detection algorithm is suitable for enhancing the quality of video acquired by consumer handheld imaging devices. © 2016 IEEE.

关键词： Stabilization

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Geometrical transformation-based ghost artifacts removing for high dynamic range image

Geometrical transformation-based ghost artifacts removing fo...

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IEEE International Conference on image processing

作者： Jaehyun Im Sangsik Jang Seungwon Lee Joonki Paik Image Processing and Intelligent System Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University South Korea

In this paper, we propose a ghost artifacts removing algorithm for obtaining artifact-free high dynamic range (HDR) images in the presence of camera movement. Existing HDR methods work on condition that there is no camera movement when acquiring multiple low dynamic range (LDR) images. For overcoming such unrealistic restriction, the proposed algorithm first specifies the target and the source images in the set of acquired LDR images, and then the source image is transformed to fit the target image by estimating translation and rotation components in the affine matrix. Therefore, the proposed algorithm can reconstruct the HDR image without ghost artifacts because camera movement is completely removed in transformed images. Experimental results show that the proposed algorithm successfully removes ghost artifacts. For this reason, the proposed algorithm can extend application areas of HDR imaging to various mobile imaging devices, such as a handheld camcorder and a mobile phone camera.

关键词： Cameras Dynamic range Heuristic algorithms image processing Erbium Software

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Hand detection using facial information

Hand detection using facial information

引用

IEEE International Conference on Consumer Electronics - Berlin (ICCE-Berlin)

作者： Sangpil Han Seokmok Park Min-jae Kim Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science and Film Chung-Ang University Seoul Korea

This paper presents a robust hand detection algorithm using the facial information. The proposed algorithm consists of four steps: (i) detection of a face, (ii) generation of regions of interest (ROI) to detect hands, (iii) skin color extraction from the face region, and (iv) detection of hands using the face skin color in the ROI. The proposed algorithm can reduce false detection caused by a similar skin color, and provides a successful detection rate up to 92 percent.

关键词： Face Skin Color Detection algorithms image color analysis Robustness Face detection

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SIMULTANEOUS OBJECT TRACKING AND DEPTH ESTIMATION USING COLOR SHIFTING PROPERTY OF A MULTIPLE COLOR-FILTER APERTURE CAMERA

SIMULTANEOUS OBJECT TRACKING AND DEPTH ESTIMATION USING COLO...

引用

IEEE International Conference on Acoustics, Speech and Signal processing

作者： Seungwon Lee Jinhee Lee Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging ScienceMultimedia and Film Chung-Ang University Seoul Korea

ISBN: (纸本)9781457705380

A multiple color-filter aperture (MCA) camera can provide depth information as well as color and intensity in the single-camera framework, where the MCA generates misalignment between color channels depending on the distance of a region-of-interest. In this paper, we present a simultaneous object tracking and depth estimation approach based on the color shifting property of an MCA camera. An object region is first extracted by using Markov Chain Monte Carlo (MCMC) sampling-based particle filter. The extracted object's region has color misalignment among RGB planes depending on the distance of the object. We estimate color shifting vectors (CSVs) between green-and-red (G-R) and green-and-blue (G-B) channels using a simplified elastic registration algorithm. Using the color shifting property of the MCA camera, the depth of the object's region is estimated from CSVs. From experimental results, we can show the MCA camera-based surveillance system can estimate depth information as well as track object.

关键词： Video surveillance particle filters image registration image color analysis image motion analysis tracking objects system buses compensatory amounts Maximum credible accidents color cast Cameras Misalignment Color SURVEILLANCE systemS

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