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International Conference on Wireless communications and Signal processing

作者： Shu Wang Feng Liu Zongliang Gan Ziguan Cui Jiangsu Province Key Lab on Image Processing & Image Communications Nanjing University of Posts and Telecommunications

ISBN: (纸本)9781509028610

Vehicle type classification has become an important part of intelligent traffic. However traditional methods can not deal with the varying situations in the reality. In this paper, a novel method is proposed to handle this task in the real road traffic surveillance video. In order to distinguish different vehicles, we categorize vehicles into three types: compact cars, mid-size cars, and heavy-duty vehicles. For a certain video, our method has four steps. First, a deep convolutional neural network is used to detect vehicles in the candidate region and a data set would be generated. Second, the main features of vehicles can be extracted using a fully-connected network. Also, for the sake of higher accuracy, weak labels given by pre-trained extreme learning machine (ELM) are fused into the final features, adding prior information proportionally. Third, K-means is implemented to learn three vehicle-type cluster centers adaptively. Finally, vehicle type will be recognized according to the closest distance principal. Experimental results show that the recognition rate outperforms other traditional methods, verifying the feasibility and effectiveness of the proposed method.

关键词： Vehicle type classification Adaptive clustering Feature learning Deep learning Extreme learning machine

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Retinex based low-light image enhancement using guided filtering and variational framework

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Optoelectronics Letters 2018年第2期14卷 156-160页

作者：张诗唐贵进刘小花罗苏淮王大东 Jiangsu Key Lab on Image Processing & Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China School of Electrical Engineering and Computing The University of Newcastle NSW 2308 Australia CSIRO Data61 PO Box 76 Epping NSW 1710 Australia

A new image enhancement algorithm based on Retinex theory is proposed to solve the problem of bad visual effect of an image in low-light conditions. First, an image is converted from the RGB color space to the HSV color space to get the V channel. Next, the illuminations are respectively estimated by the guided filtering and the variational framework on the V channel and combined into a new illumination by average gradient. The new reflectance is calculated using V channel and the new illumination. Then a new V channel obtained by multiplying the new illumination and reflectance is processed with contrast limited adaptive histogram equalization(CLAHE). Finally, the new image in HSV space is converted back to RGB space to obtain the enhanced image. Experimental results show that the proposed method has better subjective quality and objective quality than existing methods.

关键词： RGB CLAHE Retinex based low-light image enhancement using guided filtering and variational framework HSV

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A camera self-calibration method based on dual constraints of multi-view images

A camera self-calibration method based on dual constraints o...

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2011年无线通信与信号处理国际会议(WCSP 2011)

作者： Feng Liu Weiwei Han Qiong Xu Jingjing Fan Qiongjie Lin Image Processing and Image Communication Jiangsu Key Laboratory Key Lab of Broadband Wireless Commun Image Processing and Image Communication Jiangsu Key Laboratory

Camera calibration is the essential step of obtaining 3D information from 2D views in the field of computer vision, which is widely used in the area of 3D reconstruction, navigation, visual supervision, etc. A camera self-calibration method based on dual constraints of multi-view images is proposed to make calibration possible when there is no reference calibration block or the movement of camera is arbitrary. In this method, multi-view images are preprocessed first to select three images which are most suitable for camera self-calibration, then we use the method based on the genetic algorithm, the camera parameters are finally estimated by using epipolar geometry matching error and reprojection error as fitness functions as two steps. Experimental results show that the proposed camera self-calibration method is correct and effective.

关键词： multi-view images camera calibration dual constraints genetic algorithm epipolar geometry reprojection error

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A Novel Representation for Video-based Person Reidentification with Attribute-constraints

A Novel Representation for Video-based Person Reidentificati...

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International Conference on Signal processing Proceedings (ICSP)

作者： Wanru Song Jieying Zheng Yahong Wu Qingqing Zhao Changhong Chen Feng Liu Jiangsu Key Lab of Image Processing and Image Communications Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (纸本)9781538646748;9781538646731

Person re-identification is an important task in the field of intelligent video surveillance, which has become one of the research focus spots in the field of computer vision. Video-based person re-identification aims to verify a pedestrian identity of the video sequences which captured from non-overlapping cameras at different time. In this paper, we propose a novel feature extractor based on LSTM networks. These LSTM networks are used to extract the effective space-time feature representation named the attribute-constraints space-time feature (ASTF). Different from other methods, we manually annotate pedestrians in videos with three attributes. In the meantime, the attributes with the IDs of pedestrians are regarded as labels to train the feature extractor. The ASTF representation for a testing video is extracted by this feature extractor, which is an effective space-time feature representation for video-based re-identification. Extensive experiments on two public datasets demonstrate that our approach outperforms the state-of-the-art video-based re-identification methods.

关键词： Feature extraction Task analysis Training Cameras Testing Measurement Video sequences

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Error concealment for stereoscopic images using mode selection

Error concealment for stereoscopic images using mode selecti...

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International Symposium on Intelligent Signal processing and communications Systems

作者： Song, Lijuan Zhu, Xiuchang State Grid Electric Power Research Institute Nanjing 210003 China Jiangsu Province Key Lab. on Image Processing and Image Communication Nanjing University of Posts and Telecommunications Nanjing 210003 China

ISBN: (纸本)9781424473717

In this paper, a novel error concealment (EC) method for compressed stereoscopic image pairs is presented, which contains a new binocular EC mode and an improved monocular EC mode. The proposed algorithm selects appropriate EC mode to conceal the error block (EB) in the stereoscopic image according to the local characteristic of the EB. The experimental results demonstrate that the proposed scheme has good subjective and objective EC performance in stereoscopic images as compared to monocular mode. © 2010 IEEE.

关键词： Errors

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Object detection by clustering-based nonparametric kernel density estimation

Object detection by clustering-based nonparametric kernel de...

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作者： Hu, D. Hu, J. Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications China Jiangsu Province's Key Lab of Image Procession and Image Communications Nanjing University of Posts and Telecommunications China

ISBN: (纸本)9781845648282

Nonparametric model is one of the popular ones for background modeling for its ability to adapt to changes quickly in dynamic environment and enable very sensitive detection of moving objects. However, the method is too complex and computationally inefficient to real-time application. In this paper, a fast and efficient scheme for moving object detection by nonparametric background modeling was proposed, whereas the background was modeled combining clustering theory to eliminate the large amount of redundant information and noise pixels in background modeling stage. Moreover, adaptive background and temporal differencing was used to filter out unchanged background pixels, thus enabling an additional reduction in computational requirements and improving the detection results. Besides, RGB color components were substituted by chromaticity coordinates to suppress shadow effects. Experimental results demonstrated the effectiveness of the proposed algorithm. © 2014 WIT Press.

关键词： Object detection

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Research on moving object detection based on the Bayesian theory

Research on moving object detection based on the Bayesian th...

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作者： Hu, D. Liu, X. Education Ministry's Key Lab of Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications China Jiangsu Province's Key Lab of Image Procession and Image Communications Nanjing University of Posts and Telecommunications China

ISBN: (纸本)9781845648282

For effective and efficient detection of moving objects from complex surveillance scenarios, a novel integrated object detection scheme based on clustering and Bayesian theory is proposed in this paper. The algorithm conducts clustering analysis in the time domain as the pre-segmentation step for later Bayesian judgment processing. Furthermore, temporal differential image was used to classify dynamical and static pixels, which were then used to direct the Bayesian judgment with proper models. The clustering processing reduced the number of the mixture models, which in turn, reduced the computational complexity while ensuring accurate moving object detection. Simulation results show that the proposed scheme well exploited the temporal correlation of the video sequences and the accuracy of the detected objects can be improved by nearly 20% compared to the typical Gaussian mixture modeling algorithm. © 2014 WIT Press.

关键词： Object detection

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image retrieval based on character-matching technology

Image retrieval based on character-matching technology

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5th International Conference on Information Assurance and Security, IAS 2009

作者： Shan, Zhao Jing, Liu School of Computer Science and Technology Henan Polytechnic University Jiaozuo 454003 China Jiangsu Province Key Lab. on Image Processing and Image Communication Nanjing University of Posts and Communication Nanjing 210003 China

ISBN: (纸本)9780769537443

In order to introduce effective text-retrieval technologies into content-based image retrieval, a novel method based on string-matching technology was presented incorporating the different sensitivity along variant directions of human visual system. The image is firstly divided into non-overlapped blocks and sub-feature is extracted according to the human visual feature. Then, a novel descriptor is defined. Based on which, the sub-features is mapping into characters and the image into the text. Finally, the technology of the character string matching is adopted as the similarity measurement. Meantime, the situation information of character is considered, an adjusted method is proposed. Experimental results show that the proposed method has sound and robust retrieval performance. © 2009 IEEE.

关键词： Content based retrieval

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Efficient Rate Control Algorithm for Multi-view Video Coding

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China communications 2011年第3期8卷 83-89页

作者：刘峰熊婕范晶晶林琼洁 Image Processing & Image Communication Key Lab of Jiangsu Province Nanjing University of Posts and Telecommunications Key Lab of Broadband Wireless Communication and Sensor Network Technology(Nanjing University of Posts and Telecommunications) Ministry of Education

Rate control is one of the key factors influencing the multi-view video ***,there is not a rate control algorithm in the existing Joint Multi-view Video Coding *** this paper,an efficient rate control algorithm and a bit allocation strategy for multi-view video coding are *** order to obtain the consistent view quality,a bit allocation model based on the Lagrange optimum algorithm is firstly ***,considering the encoding statistical characteristics of different view types,a view weighting factor is introduced,and it will help improve the precision of bit allocation among *** with the fixed QP control strategy,experiment results show that the proposed algorithm can efficiently control the bit rate and obtain more consistent views,with video visual quality improved.

关键词： rate control rate distortion bit allocation view weighting factor

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image retrieval based on bit-plane distribution feature

Image retrieval based on bit-plane distribution feature

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6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009

作者： Shan, Zhao Jing, Lui School of Computer Science and Technology Henan Polytechnic University Jiaozuo 454003 China Jiangsu Prov. Key Lab. on Image Processing and Image Communication Nanjing University of Posts and Communication Nanjing 210003 China

ISBN: (纸本)9780769537351

Based on the analysis of color histogram for image retrieval, a new descriptor, bit-plane distribution feature(BPDF), is proposed in this paper. The image is firstly divided into eight bit-planes. Meantime, the Gray code of bit-planes is used to avoid the effect of changes in the intensity values on bit-planes. Then, according to the distribution of each bit-plane, a feature vector is constructed by the first four significant planes which contain most of the structural information of the image. Finally, the Mahalanobis distance is adopted to measure the similarity because of the correlation between the concerned vectors after designing a correlation-weighted matrix. Comparisons are conducted between BPDF and other descriptors. Experimental results show that the proposed method provides more significantly retrieval results than the traditional ones. © 2009 IEEE.

关键词： image retrieval

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