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International Conference on Machine Tool Technology and Mechatronics Engineering, ICMTTME 2014

作者： Zhang, Hao Lin Ben, Xian Ye Zhang, Peng Liu, Tian Jiao Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Nanchang Hangkong University Nanchang China School of Information Science and Engineering Shandong University Jinan China

ISBN: (纸本)9783038352464

Gait period detection, serving as a preprocessor for gait recognition, is commonly studied in the recent past. In this paper, we proposed a novel gait period detection method for depth gait video stream. The method introduces the concept of layered coding for depth images which decreases computational complexity. Furthermore, the extreme value of the sum of layered codes for gait sequence is utilized to judge the period endpoint, which is in accord with the naked-eye observation. In addition, gait recognition experiments on the TUM GAID database are conducted with the description of gait features of one single detected period by the proposed scheme using tensor representation. The high recognition accuracy verifies the effectiveness of the proposed depth gait period detection method. © (2014) Trans Tech Publications, Switzerland.

关键词： Codes (symbols)

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Gravel Image Segmentation in Noisy Background Based on Partial Entropy Method

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中国地质大学学报(英文版) 2000年第1期11卷 92-94页

作者： Wang Guangjun Tian Jinwen Chen Zhenyu Liu Jian Wu Guoping State Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology WuHan 430074 Faculty of Information Engineering China University of Geosciences Wuhan 430074

Because of wide variation in gray levels and particle dimensions and the presence of many small gravel objects in the background, as well as corrupting the image by noise, it is difficult o segment gravel objects. In this paper, we develop a partial entropy method and succeed to realize gravel objects segmentation. We give entropy principles and fur calculation methods. Moreover, we use minimum entropy error automaticly to select a threshold to segment image. We introduce the filter method using mathematical morphology. The segment experiments are performed by using different window dimensions for a group of gravel image and demonstrates that this method has high segmentation rate and low noise sensitivity.

关键词： partial entropy segmentation mathematical morphology gravel threshold filter

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A new RCNN-RF for efficient and robust parking lot available detection 16

A new RCNN-RF for efficient and robust parking lot available...

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16th International Conference on Digital Image processing, ICDIP 2024

作者： Zhang, Qian Ran, Yaqin Luo, Di Xu, Kaili Shi, Jilaing School of Data Science and Information Engineering GuiZhou MinZu University Guiyang550025 China Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guiyang550025 China

ISBN: (数字)9781510682917

ISBN: (纸本)9781510682900

It's very meaningful to conduct the driver to the parking space available in the parking lot clearly and accurately by computer vision and computational intelligence. While it is an extremely difficult task, because of the scene complexity in the parking lot. In this paper, a new computational intelligence technology is proposed to detect parking spaces available in the parking lot outdoor based on fusing of Region Convolution Neural Network (RCNN) and random forests (RF), and we called it as RCNN-RF. Within the RCNN-RF, a new activation function is design. And with the help of random forests, RCNN-RF overcomes scene complexity includes illumination, weather, and slight occlusion successfully. Extensive experimental results on the benchmark dataset named PKLot and the self-built dataset named GZMU-LOT outperform those of the state-of-the-art, and it shows the superiority of our proposed RCNN-RF method. © 2024 SPIE.

关键词： Random forests

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MRI denoising using randomized version of nonlocal means method

MRI denoising using randomized version of nonlocal means met...

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2016 International Conference on Image processing, Computer Vision, and pattern recognition, IPCV 2016

作者： Hu, Jinrong He, Jia Fu, Ying Wu, Xi Zhou, Jiliu School of Computer and Soft Engineering Xihua University Chengdu610039 China Key Laboratory of Pattern Recognition and Intelligent Information Processing Chengdu University Chengdu610106 China School of Computer Science Chengdu University of Information Technology Chengdu610225 China

ISBN: (纸本)1601324421

- Non-local mean (NLM) algorithm has been implemented effectively in MRI denoising and is always limited by its computational complexity. To reduce the computational burden of NLM in 3D MRI dataset, in this paper, we used a randomized version of NLM algorithm to remove the noise in MRI data. The random NLM algorithm seeds up the classical NLM by computing a small subset of image patch distances, which are randomly select according to the uniform sampling pattern. Numerical experiments demonstrate that the random NLM can achieve a competitive denoising result at a low sampling rate (0.05) in 3D MRI dataset while reducing the runtime dramatically. © CSREA Press.

关键词： Magnetic resonance imaging

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Fast DCT-I, DCT-III, and DCT-IV via Moments

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Eurasip Journal on Applied Signal processing 2005年第12期2005卷 1902-1909页

作者： Liu, J.G. Liu, Y.Z. Wang, G.Y. Key Laboratory of Education Huazhong University of Science and Technology Ministry for Image Processing and Intelligence Control Wuhan 430074 China Department of Computer Science and Engineering China University of Geosciences Wuhan 430074 China Key Laboratory of State Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology China Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology China

This paper presents a novel approach to compute DCT-I, DCT-III, and DCT-IV. By using a modular mapping and truncating, DCTs are approximated by linear sums of discrete moments computed fast only through additions. This enables us to use computational techniques developed for computing moments to compute DCTs efficiently. We demonstrate this by applying our earlier systolic solution to this problem. The method can also be applied to multidimensional DCTs as well as their inverses. © 2005 Hindawi Publishing Corporation.

关键词： Method of moments

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Contour-based multisensor image registration using gradient vector features

Contour-based multisensor image registration using gradient ...

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MIPPR 2009 - Automatic Target recognition and Image Analysis: 6th International Symposium on Multispectral Image processing and pattern recognition

作者： Ming, Delie Wang, Mi Gao, Pengfei State Key Laboratory for Multi-spectral Information Processing Technology Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan Hubei Province 430074 China

ISBN: (纸本)9780819478061

Multi-sensor image registration plays an important role in the automatic targets acquirement (ATA). In this paper, two kinds of new multi-sensor image registration methods based on contour feature are put forward. One is gradient vector correlation coefficient method which is based on contour characteristics of the image, the other is called relative gradient difference method which is in fact a measurement of differences between out-contour area and inner area of the target. Lots of experimental data composed of satellite images and real-time infrared images are used to verify the above two algorithms, and the results show that the two proposed methods can have good performances for both day and night infrared images. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Image registration

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Video Compression Artifacts Removal With Spatial-Temporal Attention-Guided Enhancement

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IEEE Transactions on Multimedia 2024年 26卷 5657-5669页

作者： Jiang, Nanfeng Chen, Weiling Lin, Jielian Zhao, Tiesong Lin, Chia-Wen Fujian Key Laboratory for Intelligent Processing and Wireless Transmission of Media Information Fuzhou University Fuzhou350108 China Fujian Key Laboratory of Pattern Recognition and Image Understanding Xiamen University of Technology Xiamen361024 China Fujian Science and Technology Innovation Laboratory for Optoelectronic Information of China Fuzhou350116 China Department of Electrical Engineering National Tsing Hua University Hsinchu30013 Taiwan Institute of Communications Engineering National Tsing Hua University Hsinchu30013 Taiwan

Recently, many compression algorithms are applied to decrease the cost of video storage and transmission. This will introduce undesirable artifacts, which severely degrade visual quality. Therefore, Video Compression Artifacts Removal (VCAR) aims at reconstructing a high-quality video from its corrupted version of compression. Generally, this task is considered as a vision-related instead of media-related problem. In vision-related research, the visual quality has been significantly improved while the computational complexity and bitrate issues are less considered. In this work, we review the performance constraints of video coding and transfer to evaluate the VCAR outputs. Based on the analyses, we propose a Spatial-Temporal Attention-Guided Enhancement Network (STAGE-Net). First, we employ dynamic filter processing, instead of conventional optical flow method, to reduce the computational cost of VCAR. Second, we introduce self-attention mechanism to design Sequential Residual Attention Blocks (SRABs) to improve visual quality of enhanced video frames with bitrate constraints. Both quantitative and qualitative experimental results have demonstrated the superiority of our proposed method, which achieves high visual qualities and low computational costs. © 2023 IEEE.

关键词： Computational complexity

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Challenging the recognition of facial expression via deep learning

Challenging the recognition of facial expression via deep le...

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作者： Hu, De Kun Liu, Yong Hong Zhang, Li Duan, Gui Duo Key Laboratory of Pattern Recognition and Intelligent Information Processing Institutions of Higher Education of Sichuan Province Chengdu University Chengdu 610106 China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 610054 China

ISBN: (纸本)9783038351399

A deep Neural Network model was trained to classify the facial expression in unconstrained images, which comprises nine layers, including input layer, convolutional layer, pooling layer, fully connected layers and output layer. In order to optimize the model, rectified linear units for the nonlinear transformation, weights sharing for reducing the complexity, "mean" and "max" pooling for subsample, "dropout" for sparsity are applied in the forward processing. With large amounts of hard training faces, the model was trained via back propagation method with stochastic gradient descent. The results of shows the proposed model achieves excellent performance. © (2014) Trans Tech Publications, Switzerland.

关键词： Neural network models

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A novel approach to edge detection of color image based on quaternion fractional directional differentiation

A novel approach to edge detection of color image based on q...

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2011 International Conference on Automation and Robotics, ICAR 2011

作者： Gao, Chaobang Zhou, Jiliu Lang, Fangnian Pu, Qiang Liu, Chang College of Computer Science and Technology Chengdu University Chengdu 610106 China School of Computer Science Sichuan University Chengdu 610064 China Key Laboratory of Pattern Recognition and Intelligent Information Processing Sichuan Province Chengdu 610106 China

ISBN: (纸本)9783642255526

In this paper, we denote a color image by a quaternion function, then find edge points by solving the maximum of quaternion fractional directional differentiation(QFDD)'s norm. This method is called edge detection based on QFDD. Experiments indicate that the method has special advantages. Comparing with Canny, LOG, Sobel, and general fractional differentiation, we discover that QFDD has fewer false negatives in the textured regions and is also better at detecting edges which are partially defined by texture, which means we will obtain better results in the interesting regions by QFDD and these results are more consistent with the characteristics of human visual system. © 2011 Springer-Verlag.

关键词： Edge detection

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New lower bounds for two multicolor vertex Folkman numbers

New lower bounds for two multicolor vertex Folkman numbers

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International Conference on Computer and Management

作者： Shao, Zehui Liang, Meilian He, Jiandong Xu, Xiaodong School of Information Science and Technology Chengdu University Chengdu 610106 China Key Laboratory of Pattern Recognition and Intelligent Information Processing Sichuan Province China School of Mathematics and Information Science Guangxi University Nanning 530004 China Guangxi Academy of Sciences Nanning 530007 China

For a graph G, G → (a1, a2, · · ·, ar)v means that in every r-coloring of the vertices in G, there exists a monochromatic ai-clique of color i for some i∈{1, 2, · · ·, r}. The vertex Fo... 详细信息

ISBN: (纸本)9781424492831

For a graph G, G → (a1, a2, · · ·, ar)v means that in every r-coloring of the vertices in G, there exists a monochromatic ai-clique of color i for some i∈{1, 2, · · ·, r}. The vertex Folkman number is defined as Fv(a1, a2, ···, ar;k) = min{|V(G)|: G → (a1, a2, ···, ar)v and Kk G}. In general, computing lower and upper bounds for vertex Folkman numbers is difficult. In this note, based on theoretical analysis and computation, we show that Fv(2, 3, 3;4) ≥ 19 and Fv(3, 3, 3;4) ≥ 24, and suggest a cyclic graph of order 91 which may give an upper bound for Fv(3, 3, 3;4). ©2011 IEEE.

关键词： Graph theory

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