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检索条件"任意字段=2013 IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2013"

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What's the Role of Image Matting in Image Segmentation?

What's the Role of Image Matting in Image Segmentation?

引用

ieee International conference on Robotics and Biomimetics

作者： Qingsong Zhu Pheng Ann Heng Ling Shao Xuelong Li Shenzhen Institutes of Advanced Technology Chinese Advanced of Sciences Shenzhen China Department of Computer Science and Engineering Ho Sin-Hang Engineering Building Shatin Hong Kong N.T Department of Electronic and Electrical Engineering The University of Sheffield Sheffield UK Centre for OPTical IMagery Analysis and Learning (OPTIMAL) Chinese Academy of Sciences Xi'an Shanxi P.R. China

ISBN: (纸本)9781479927456

Image Matting is the key technology in image processing, video editing, and film-making applications. With the fast development of modern information technology, image matting has gained increasing interests from both academic and industrial communities. So what is Image Matting? And, What's the Role of Image Matting in Image Segmentation? In this paper, we will try to give a comprehensive and constructive answer to the above questions.

关键词： Image segmentation conferences computer vision Equations Image color analysis pattern recognition Patents

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Class representative computation using graph embedding and clustering

Class representative computation using graph embedding and c...

引用

ieee Signal Processing and Communications Applications (SIU)

作者： Fahri Aydos M. Fatih Demirci Bilgisayar Mühendisliği Bölümü TOBB Ekonomi ve Teknoloji Üniversitesi Ankara Turkey

One of the methods for object recognition is based on graph embedding. By representing objects expressed as graphs into the vector space, this technique makes it possible to use point matching algorithms as opposed to costly graph matching approaches. In this paper, representatives of object classes in the vector space is obtained through graph embedding. To classify a query, instead of using exhaustive search, a more effective way of comparing it to class representatives is employed. Experimental results demonstrate that the proposed work compares favorably to alternative approaches in a set of object recognition experiments.

关键词： Object recognition pattern recognition Algorithm design and analysis Support vector machine classification Biology Shape computer vision

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Propagation for feature matching using triangular constraints

Propagation for feature matching using triangular constraint...

引用

ieee International conference on Robotics and Biomimetics

作者： Qike Shao Sheng Liu Shengyong Chen College of Computer Science and Technology Zhejiang University of Technology Hangzhou China

ISBN: (纸本)9781479927456

This paper presents a novel Matching Propagation Framework for addressing the problem of finding better matching pairs between each two images, which is one of the most fundamental tasks in computer vision and pattern recognition. We first select initial seed points by original matching method like SIFT, and then use T-CM to explore more seed points. Finally, a triangle constraint based quasi-dense algorithm is adopted to propagate better matches around seed points. The experimental evaluation shows that our method can get a more precise matching result than classical quasi-dense algorithm. And the 3D reconstruction of the scene from our method has a good visual effect. Both experiments demonstrate the robust performance of our method.

关键词： Three-dimensional displays Accuracy Feature extraction Reliability Algorithm design and analysis Image reconstruction Visual effects

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Video mosaicing of planer scenes using extended kalman filter

Video mosaicing of planer scenes using extended kalman filte...

引用

ieee Signal Processing and Communications Applications (SIU)

作者： Emrecan Batı Yeti Ziya Gürbüz A. Aydın Alatan Elektrik ve Elektronik Mühendisliği Bölümü Orta Doğu Teknik Üniversitesi Ankara Turkey

In this work, the large planar scene is reconstructed from small images. Small images can be consecutive video frames or sequence of photographs. In the problem, called mosaicing, instead of using widely used optimization based methods, probabilistic methods are used in the proposed method. Simultaneous Localization And Mapping(SLAM) techniques are adapted for video mosaicing. Probabilistic measures for the landmark locations are used to merge small images to create large scene. Experimental tests give promising results if the performance-complexity is considered at the same time.

关键词： Kalman filters computer vision Probabilistic logic Art pattern recognition ieee computer Society conferences

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Social risk and depression: Evidence from manual and automatic facial expression analysis

Social risk and depression: Evidence from manual and automat...

引用

International conference on Automatic Face and Gesture recognition

作者： Jeffrey M. Girard Jeffrey F. Cohn Mohammad H. Mahoor Seyedmohammad Mavadati Dean P. Rosenwald Department of Psychology University of Pittsburgh USA Robotics Institute Carnegie Mellon University USA Department of Electrical and Computer Engineering University of Denver USA

ISBN: (纸本)9781467355452

Investigated the relationship between change over time in severity of depression symptoms and facial expression. Depressed participants were followed over the course of treatment and video recorded during a series of clinical interviews. Facial expressions were analyzed from the video using both manual and automatic systems. Automatic and manual coding were highly consistent for FACS action units, and showed similar effects for change over time in depression severity. For both systems, when symptom severity was high, participants made more facial expressions associated with contempt, smiled less, and those smiles that occurred were more likely to be accompanied by facial actions associated with contempt. These results are consistent with the “social risk hypothesis” of depression. According to this hypothesis, when symptoms are severe, depressed participants withdraw from other people in order to protect themselves from anticipated rejection, scorn, and social exclusion. As their symptoms fade, participants send more signals indicating a willingness to affiliate. The finding that automatic facial expression analysis was both consistent with manual coding and produced the same pattern of depression effects suggests that automatic facial expression analysis may be ready for use in behavioral and clinical science.

关键词： Gold Interviews Attenuation Manuals Encoding Context Reliability

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3D palmprint pose estimation using stereo camera

3D palmprint pose estimation using stereo camera

引用

ieee Signal Processing and Communications Applications (SIU)

作者： Özkan Bingöl Murat Ekinci Yazílím Mühendisliği Bölümü Gümüşhane Üniversitesi Gumushane Turkey Bilgisayar Mühendisliği Bölümü Karadeniz Teknik Üniversitesi Trabzon Turkey

Although studies on the palm recognition systems achieving are high performance ratios, hygiene problems in contact systems and change of hand pose in contactless systems were encountered. 3D recognition systems is proposed for solve these problems. But, these systems did not find the opportunity to become widespread because of expensive technologies and low scanning speed. In this study was proposed a method for determined pose variations of palmprint using stereo cameras and transferring patterns that to be used for recognition to 2D space. Thus, both a non-contact system will be obtained and can be used properties of strong 2D recognition systems.

关键词： Cameras Three-dimensional displays Geometry computer vision pattern recognition Robustness Authentication

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Lightweight sign recognition for mobile devices

Lightweight sign recognition for mobile devices

引用

ACM/ieee International conference on Distributed Smart Cameras, ICDSC

作者： Michele Fornaciari Andrea Prati Costantino Grana Rita Cucchiara Universita degli Studi di Modena e Reggio Emilia Modena Emilia-Romagna IT DPPAC University IUAV of Venice 30135 Italy

The diffusion of powerful mobile devices has posed the basis for new applications implementing on the devices (which are embedded devices) sophisticated computer vision and pattern recognition algorithms. This paper describes the implementation of a complete system for automatic recognition of places localized on a map through the recognition of significant signs by means of the camera of a mobile device (smartphone, tablet, etc.). The paper proposes a novel classification algorithm based on the innovative use of bag-of-words on ORB features. The recognition is achieved using a simple yet effective search scheme which exploits GPS localization to limit the possible matches. This simple solution brings several advantages, such as the speed also on limited-resource devices, the usability also with limited training samples and the easiness of adapting to new training samples and classes. The overall architecture of the system is based on a REST-JSON client-server architecture. The experimental results have been conducted in a real scenario and evaluating the different parameters which influence the performance.

关键词： Vectors Servers Mobile handsets computer architecture Training Histograms Hamming distance

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Workpiece localization with shadow detection and removing

Workpiece localization with shadow detection and removing

引用

ieee International conference on Robotics and Biomimetics

作者： Zhengke Qin Wenjun Zhu Peng Wang Hong Qiao Research Center of Precision Sensing and Control Chinese Academy of Sciences Beijing

ISBN: (纸本)9781479927456

This paper presents a new approach to detect and remove the shadows for workpiece localization, which is with an extensive application in automatic assembly system. However, the shadows of workpiece will badly affect this procedure as the contour of the shadow has the same shape with the workpiece itself in the image. The localization system treats the shadow as a part of the workpiece and make incorrect decision. So removing the shadow in the image before localization is meaningful. Our approach use CAD model to estimate the pose of workpiece, and the contour of object can be drawn in the image. Gray and texture features are used to detect and remove the shadow around the workpiece, and the workpiece is localized without the disturbance of the shadow in image. Experiments have been designed and performed. The experimental results demonstrate the effectiveness of the proposed method.

关键词： Estimation Feature extraction Solid modeling pattern recognition computer vision Lighting

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A pedestrian detection system with weak classifiers

A pedestrian detection system with weak classifiers

引用

ieee Signal Processing and Communications Applications (SIU)

作者： Yusuf Engin Tetik Bülent Bolat Multimedya Sinyal Analiz Laboratuarı Elektronik ve Haberleşme Müh. Bl. Yıldız Teknik Üniversitesi Istanbul Turkey

In this paper, a pedestrian detection system which uses sliding window approach to detect pedestrians in still digital images is presented. The proposed pedestrian detection system combines weak classifiers in an Adaboost like novel way to create a strong classifier. Besides, rectangle ratios and discrete cosine transform coefficients are used as features with the well-known rectangle differences method.

关键词： Boosting computer vision pattern recognition computers conferences Abstracts Digital images

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A semantic model for video based face recognition

A semantic model for video based face recognition

引用

International conference on Information and Automation (ICIA)

作者： Dihong Gong Kai Zhu Zhifeng Li Yu Qiao Shenzhen Key Lab of Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences The Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9781479913329

Video-based face recognition has attracted a great deal of attention in recent years due to its wide applications. The challenge of video-based face recognition comes from several aspects. First, video data involves many frames, which increases data size and processing complexity. Second, key frames extracted from videos are usually of high intra-personal discrepancy due to variations in expressions, poses, and illuminations. In order to address these problems, we propose a novel semantic based subspace model to improve the performance of video based face recognition. The basic idea is to construct an appropriate low-dimensional subspace for each person, upon which a semantic model is built to classify the key frames of the person into specific class. After the semantic classification, the key frames belonging to the same classes, i.e. the same semantics, are used to train the linear classifiers for recognition. Extensive experiments on a large face video database (XM2VTS) clearly show that our approach obtains a significant performance improvement over the traditional approaches.

关键词： Face Training Face recognition Semantics Video sequences Principal component analysis Probes

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