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Content-based image quality assessment of natural scene image distorted by quantization

Content-based image quality assessment of natural scene imag...

引用

IEEE Visual Communications and image processing (VCIP)

作者： Tao Luo Chao Wang Xuanqin Mou Institute of Image Processing and Pattern Recognition Xi'an Jiaotong University Xi'an China

In this paper, the subjective image quality for different image content is investigated by psychophysical experiments. The experimental images are the parts from natural scenes distorted by integer transform and quantization in H.264 frame. These images are divided into two types based on the scene content, type I and type II. The perceived thresholds and subjective graded scores for different quantization are obtained using forced choice staircase experiments and graded response experiments, respectively. The subjective assessment results showed that the image quality of type I degrades much more than the type II when quantization steps increase, and the preliminary experiment showed that the existed IQA metric, i.e. SSIM, could not predict it well. We also present a content-based image classifier to predict the two image types. The results show good accordance between the classifier and the subjective assessment.

关键词： Quantization image quality Measurement image edge detection Transforms Histograms image coding

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A Real Time Object Tracking Approach for Mobile Robot Visual Servo Control

A Real Time Object Tracking Approach for Mobile Robot Visual...

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第一届亚洲模式识别会议

作者： Zhaoxiang Zhang Yunhong Wang Ruhan Sa Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media

ISBN: (纸本)9781457701221

A key problem of image Based Visual Servo (IBVS) System is to track objects in image sequences. Thus, the tracking algorithm plays an important role in improving the efficiency of IBVS systems. In this paper, a novel tracking algorithm called Modified CamShift Guided Particle Filter (MCAMSGPF) is proposed, which interpolated Speeded-Up Robust Features (SURF) into the framework of conventional CamShift Guided Particle Filter (CAMSGPF) tracking method. This new algorithm outperforms conventional CAMSGPF and other baseline trackers with respect to tracking robustness in the clutter background of similar colors and occlusions. We also proposed a new system model to implement and test the new algorithm in a real time moving IBVS system, which is applied in a mobile robot with an on-board camera.

关键词： Robustness image color analysis Robots Target tracking Cameras Clutter

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Multi-view Moving Objects Classification via Transfer Learning

Multi-view Moving Objects Classification via Transfer Learni...

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第一届亚洲模式识别会议

作者： Jianyun Liu Zhaoxiang Zhang Yunhong Wang Yi Mo Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media

ISBN: (纸本)9781457701221

Moving objects classification in traffic scene videos is a hot topic in recent years. It has significant meaning to intelligent traffic system by classifying moving traffic objects into pedestrians, motor vehicles, non-motor vehicles etc.. Traditional machine learning approaches make the assumption that source scene objects and target scene objects share same distributions, which does not hold for most occasions. Under this circumstance, large amount of manual labeling for target scene data is needed, which is time and labor consuming. In this paper, we introduce TrAdaBoost, a transfer learning algorithm, to bridge the gap between source and target scene. During training procedure, TrAdaBoost makes full use of the source scene data that is most similar to the target scene data so that only small number of labeled target scene data could help improve the performance significantly. The features used for classification are Histogram of Oriented Gradient features of the appearance based instances. The experiment results show the outstanding performance of the transfer learning method comparing with traditional machine learning algorithm.

关键词： Feature extraction Training image edge detection Training data Accuracy Videos Support vector machines

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Saliency Model Based Head Pose Estimation by Sparse Optical Flow

Saliency Model Based Head Pose Estimation by Sparse Optical ...

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第一届亚洲模式识别会议

作者： Chao Wang Tao Xu Yunhong Wang Zhaoxiang Zhang Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media

Head pose plays an important role in Human- Computer interaction, and its estimation is a challenge problem compared to face detection and recognition in computer vision. In this paper, a novel and efficient method is proposed to estimate head pose in real-time video sequences. A saliency model based segmentation method is used not only to extract feature points of face, but also to update and rectify the location of feature points when missing happened. This step also gives a benchmark for vector generation in pose estimation. In subsequent frames feature points will be tracked by sparse optical flow method and head pose can be determined from vectors generated by feature points between successive frames. Via a voting scheme, these vectors with angle and length can give a robust estimation of the head pose. Compared with other methods, annotated training data set and training procedure is not essential in our method. Initialization and re-initialization can be done automatically and are robust for profile head pose. Experimental results show an efficient and robust estimation of the head pose.

关键词： Face Estimation Magnetic heads Optical imaging Computer vision Skin

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View-invariant Action recognition in Surveillance Videos

View-invariant Action Recognition in Surveillance Videos

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第一届亚洲模式识别会议

作者： Fang Zhang Zhaoxiang Zhang Yunhong Wang Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media

ISBN: (纸本)9781457701221

Recently, human action recognition has been a popular and important topic in computer vision. However, except some conventional problems such as noise, low resolution etc., viewinvariant recognition is one of the most challenging problems. In this paper, we focus on solve multi-view action recognition from surveillance video. To detect moving objects from complicated backgrounds, this paper employs improved Gaussian mixed model, which uses K-means clustering to initialize the model and it gets better motion detection results for surveillance videos. We demonstrate the silhouette representation ”Envelope Shape” can solve the viewpoint problem in surveillance videos. The experiment results demonstrate that our human action recognition system is fast and efficient on CASIA activity analysis database.

关键词： Videos Gaussian distribution Surveillance Shape Humans Hidden Markov models Databases

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Interesting Region Detection in Aerial Video Using Bayesian Topic Models

Interesting Region Detection in Aerial Video Using Bayesian ...

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第一届亚洲模式识别会议

作者： Jiewei Wang Yunhong Wang Zhaoxiang Zhang Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media

ISBN: (纸本)9781457701221

Searching interesting regions in aerial video is a new and challenging problem. This paper presents an approach to detect visual interesting regions in aerial video using pLSA topic model. Traditional interesting region detection approaches just use bottom-up information, such as color, orientation and movement etc. Our proposed method can discover the semantic content of the whole image, the co-occurrence of local image patches via pLSA model, and consequently improve detection result significantly in real world scenes. First, we extract frames from aerial video as documents. Then we use vector quantized SIFT descriptors as words. Third, we discover topics (e.g. plants, roads, buildings) and the relation among them using pLSA model. Finally, we can detect interesting regions as we need according to calculated models. Experimental observations show the success of our approach on interesting region detection in aerial video.

关键词： Visualization Histograms Detectors Semantics Observers Vectors Vocabulary

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Maintaining imbalance highly dependent medical data using dirichlet process data generation

Maintaining imbalance highly dependent medical data using di...

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International Conference on Digital Information Management (ICDIM)

作者： Tieta Antaresti Mohamad Ivan Fanany Aniati Murni Arymurthy Pattern Recognition Image Processing and Content-Based Image Retrieval Laboratory Faculty of Computer Science Universitas Indonesia Depok Indonesia

The existence of imbalanced data between one class and another class is an important issue to be considered in a classification problem. One of the well-known data balancing technique is the artificial oversampling, which increase the size of datasets. In this research, multinomial classification was applied to classify some recorded features obtained from a single ECG (electrocardiograph) sensor. Therefore, a Dirichlet process, a dirichlet distribution of cumulative distribution function of each data partition, was needed to model the distribution of the new generated data by also considering the statistical properties of the previous data. Data balancing process had given the result of 77.21% classification accuracy (CA), and 90.9% area under ROC curve (AUC).

关键词： Electrocardiography Accuracy Diseases Data models Bayesian methods Sleep apnea Machine learning

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A Traffic Flow Detection System Combining Optical Flow and Shadow Removal

A Traffic Flow Detection System Combining Optical Flow and S...

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第三届全国智能视觉监控学术会议

作者： Yunhong Wang Zhaoxiang Zhang Yuqing Hou Jie Qin Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital MediaB

ISBN: (纸本)9781457718342

Traffic flow detection plays an important role in Intelligent Transportation Systems(ITS).Video based traffic flow detection system is the most widely used strategy in *** this circumstance,we design and implement a video based traffic flow detection system which is called MyTD in this *** takes advantages of both shadow removal and optical flow ***,we introduce the current development of ITS and focus on the video based traffic detection technology,which is the key to ***,a shadow removal algorithm combining information in both RGB and HSV color spaces is ***,based on the Iterative Pyramidal LK Optical Flow Algorithm,a vehicle tracking function is realized by OpenCV,as well as a Connected Components Labeling function and the vehicle counting ***,MyTD is implemented and tested based on the algorithm presented *** results show the outstanding performance of our method comparing with traditional optical flow algorithms.

关键词： Optic Flow Traffic flow Videotapes Detection systems connected component shadows red-green-blue colour model Intelligent Tutoring Systems Intelligent transportation systems

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Research on large-scale scene infrared simulation based on image classification

Research on large-scale scene infrared simulation based on i...

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International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping

作者： Zou, Lamei Zhang, Tianxu Lv, Wei Ao, Guoqing Institute for Pattern Recognition and Artificial Intelligence Natl. Key Laboratory of Science and Technology on Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781424494040

Vega has been widely used in Virtual Reality (VR) field. Vega infrared (IR) module can implement IR simulation, but Vega IR imaging simulation's general approach does not apply to large-scale scene's infrared simulation problem. This article deeps into large-scale scene IR image simulation through Vega infrared module based on visible image, the scene's corresponding Digital Elevation Model (DEM) data and targets' 3D model. A real time large-scale IR simulation system is successfully designed and realized in this paper. At the aspect of image classification, a coarse to fine k-means clustering method based on the consistency of image color is proposed. The proposed automatic texture material mapping method based on the development of Vega TMM tool provides a fast and convenient way for large-scale scene's IR simulation based on Vega IR module. And finally, results of the large-scale scene infrared simulation show the effectiveness of this method. ©2011 IEEE.

关键词： image classification

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Accurate moving object detection in thermal imagery

Accurate moving object detection in thermal imagery

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IEEE International Conference on Computer Science and Automation Engineering (CSAE)

作者： Zhang, Yan Zhao, Ting Gu, Jian Yu, Shengyang Testing Center of Security Products for Computer Information System Ministry of Public Security Quality Supervision Ministry of Public Security Shanghai China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)9781424487257

Accurate detection of moving object provides a fundamental capability that drives numerous high-level computer vision applications. In this paper, a novel algorithm is proposed to detect objects in widely varying thermal imagery. On the basis of properties of thermal imagery, effective foreground and background model are first presented, and then these models are competitively used in an unified MAP-MRF framework to detect objects. Experimental results on challenging dataset show the robustness and effectivity of the proposed algorithm. © 2011 IEEE.

关键词： Object detection

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