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Canadian Conference on Computer and Robot Vision, CRV

作者： Amir H. Shabani John S. Zelek David A. Clausi Vision and Image Processing Laboratory Intelligent Systems Laboratory University of Waterloo ONT Canada Intelligent Systems Laboratory University of Waterloo ONT Canada Vision and Image Processing Laboratory University of Waterloo ONT Canada

This paper proposes an extension to anisotropic diffusion filtering for a better preservation of semantically meaningful structures such as edges in an image in its smoothing/denoising process. The problem of separation of the gradients due to edges and the gradients due to noise is formulated as a nonlinearly separable classification problem. More specifically, the spatially-regularized image gradient is mapped to a higher dimensional Reproducing Kernel Hilbert Space (RKHS) in which the gradients of the edges from those of noise can be readily separated. This proper discrimination of edges prevents the filter from blurring the edges, while smoothing the image. Compared to the existing anisotropic filters, the proposed method improves the denoising and smoothing of an image on both synthetic and real images.

关键词： image edge detection Anisotropic magnetoresistance Kernel Smoothing methods Noise Noise reduction Design automation

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Evaluation of Local Spatio-temporal Salient Feature Detectors for Human Action Recognition

Evaluation of Local Spatio-temporal Salient Feature Detector...

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Canadian Conference on Computer and Robot Vision, CRV

作者： Amir H. Shabani David A. Clausi John S. Zelek Vision and Image Processing Laboratory Intelligent Systems Laboratory University of Waterloo ONT Canada Vision and Image Processing Laboratory University of Waterloo ONT Canada Intelligent Systems Laboratory University of Waterloo ONT Canada

Local spatio-temporal salient features are used for a sparse and compact representation of video contents in many computer vision tasks such as human action recognition. To localize these features (i.e., key point detection), existing methods perform either symmetric or asymmetric multi-resolution temporal filtering and use a structural or a motion saliency criteria. In a common discriminative framework for action classification, different saliency criteria of the structured-based detectors and different temporal filters of the motion-based detectors are compared. We have two main observations. (1) The motion-based detectors localize features which are more effective than those of structured-based detectors. (2) The salient motion features detected using an asymmetric temporal filtering performbetter than all other sparse salient detectors and dense sampling. Based on these two observations, we recommend the use of asymmetric motion features for effective sparse video content representation and action recognition.

关键词： Feature extraction Detectors Humans Training Cameras Standards Accuracy

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An Approach with Nested Partition for Resource-Constrained Project Scheduling Problem

An Approach with Nested Partition for Resource-Constrained P...

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2012 IEEE 19th International Conference on Industrial Engineering and Engineering Management(IE&EM 2012)

作者： Zhen-yuan Liu Wen-min Yu Institute of Systems Engineering Huazhong University of Science and Technology Key Laboratory of Education Ministry for Image Processing and Intelligent Control

A time-based nested partition （NP） approach is proposed to solve resource-constrained project scheduling problem （RCPSP） in this paper. In iteration, one activity is selected as the base point of which the finish time interval calculated by CPM is divided into two parts to form two subregions on the basis of the promising region of the last iteration. Then sampling is taken in both subregions and the surrounding region to determine the promising region and aggregate the other as the surrounding region of this iteration so that whether the backtracking or the moving operation being performed is determined. Double justification is also performed in iteration to improve the results. The results of numerical tests on PSPLIB show the effectiveness and time-efficient of the proposed NP method.

关键词： Double justification nested partition RCPSP sampling

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Single camera-based full depth map estimation using color shifting property of a multiple color-filter aperture

Single camera-based full depth map estimation using color sh...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Seungwon Lee Junghyun Lee Monson H. Hayes Aggelos K. Katsaggelos Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea Department of Electrical Engineering and Computer Science Northwestern University Evanston IL USA

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 single camera-based estimation of the full depth map using the color shifting property of the MCA. For estimating the color shifting vectors (CSVs) among red, green, and blue color channels, edges are extracted at each color channel. At the edge, we estimate CSVs using normalized cross correlation combined with color shifting mask map. A full depth map is then generated by depth interpolation using the matting Laplacian method from sparsely estimated CSVs at an edge location. Experimental results show that the proposed method can not only estimate the full depth map but also correct the misaligned color image to generate photorealistic color images using a single camera equipped with MCA.

关键词： image color analysis Cameras Estimation Channel estimation image edge detection Interpolation Apertures

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An Iterative Procedure for Multidimensional Realization By LFT Techniques

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IFAC Proceedings Volumes 2012年第13期45卷 723-727页

作者： Huijin Fan Li Xu Kose Uemura Shinya Matsushita Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Dept. Control Science & Engineering Huazhong University of Science and Technology P. R. China Dept. of Electronic and Information Systems Akita Prefectural University Akita Japan

In this paper, by utilizing Linear Fractional Transformation (LFT) techniques, an iterative realization procedure resulting in multidimensional ( n -D) Roesser state-space model is proposed. The philosophy employed here is to achieve an overall n -D realization by realizing relatively lower-dimensional systems with respect to (w.r.t.) less-number of variables iteratively. Symbolic examples are presented to illustrate the basic idea as well as the effectiveness of the proposed procedure.

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REGULARIZED ADAPTIVE SUPER-RESOLUTION USING KERNEL ESTIMATION-BASED EDGE RECONNECTION AND KERNEL ORIENTATION CONSTRAINTS

REGULARIZED ADAPTIVE SUPER-RESOLUTION USING KERNEL ESTIMATIO...

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IEEE International Conference on image processing

作者： Jaehwan Jeon Jinhee Lee Eunsung Lee Monson H. Hayes Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University (CAU) Seoul South Korea 1st Research and Development Center/CP group Nextchip Company Limited Seoul South Korea

This paper presents a spatially adaptive super-resolution (SR) algorithm using homogeneous region analysis for minimizing undesired interpolation artifacts such as aliasing and jagged edges. The proposed regularized SR algorithm incorporates two constraints enforcing (i) disconnected edges to be reconnected and (ii) orientation-adaptive regularization. By combining two constraints in the regularization framework, the proposed SR algorithm can significantly reduce aliasing artifacts and, as a result, produce edge-preserved high-resolution (HR) images. In addition to the formulation of the regularized SR algorithm with hybrid constraints, experimental results show that the proposed SR algorithm improves peak-to-peak signal-to-noise ratio (PSNR) of the reconstructed HR images by up to 5[dB]over existing state-of-the-art SR methods.

关键词： image edge detection Kernel image reconstruction Estimation Filtering algorithms Maximum likelihood detection image resolution

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Visual saliency based aerial video summarization by online scene classification

Visual saliency based aerial video summarization by online s...

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International Conference on image and Graphics

作者： Wang, Jiewei Wang, Yunhong Zhang, Zhaoxiang Laboratory of Intelligent Recognition and Image Processing Beihang University Beijing China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China

ISBN: (纸本)9780769545417

Compared with traditional video summarization approaches, aerial video summarization is a new and challenging issue for its particular characteristics. Aerial video data is a massive data stream, without pre-edit structures such as sports or news video data, lack of camera motion such as zoom and pan. On account of these characteristics, we proposed a novel approach for summarization. First, we extract GIST features for each frame as the holistic scene representation. Then, we divide aerial video into temporal segments representing a visual scene using on-line clustering method by examine GIST features of each frame only once. Finally, we select several key frames from each scene for summarization according to visual saliency index (VSI) of each frame computed from their visual saliency map. In the paper, we proposed new criterion for estimation of temporal segmentation of streaming video. Experimental observations show the success of our approach on aerial video summarization. © 2011 IEEE.

关键词： Antennas

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Peripheral region enhancement of geometrically compensated images from a fisheye lens

Peripheral region enhancement of geometrically compensated i...

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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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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...

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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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Vaguelette-wavelet decomposition for real-time image restoration using directional wavelet bases

Vaguelette-wavelet decomposition for real-time image restora...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Wonseok Kang Eunsung Lee Sangjin Kim Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea

Conventional image restoration filters, such as Wiener filter, often exhibit either noise amplification or over-smoothing problem. On the other hand, advanced image restoration techniques, such as iterative regularization or combined Fourier and wavelet domain thresholding techniques, is not suitable for real-time application because of high computational overhead. For overcoming these problems, we adopt vaguelette-wavelet decomposition (VWD) approach to realtime, space-frequency adaptive image restoration based on the estimated point spread-function (PSF) and directional wavelet bases.

关键词： image restoration Wavelet transforms Low pass filters Filtering algorithms Real time systems Noise

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