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检索条件"任意字段=International Conference on Computer Vision and Image Processing, CVIP 2016"

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Automatic 3D Car Model Alignment for Mixed image-Based Rendering

Automatic 3D Car Model Alignment for Mixed Image-Based Rende...

引用

international conference on 3D Imaging, Modeling, processing, Visualization and Transmission (3DIMPVT)

作者： Rodrigo Ortiz-Cayon Abdelaziz Djelouah Francisco Massa Mathieu Aubry George Drettakis INRIA Ecole des Ponts ParisTech

ISBN: (纸本)9781509054084

image-Based Rendering (IBR) allows good-quality free-viewpoint navigation in urban scenes, but suffers from artifacts on poorly reconstructed objects, e.g., reflective surfaces such as cars. To alleviate this problem, we propose a method that automatically identifies stock 3D models, aligns them in the 3D scene and performs morphing to better capture image contours. We do this by first adapting learning-based methods to detect and identify an object class/pose in images. We then propose a method which exploits all available information, namely partial and inaccurate 3D reconstruction, multi-view calibration, image contours and the 3D model to achieve accurate object alignment suitable for subsequent morphing. These steps provide models which are well-aligned in 3D and to contours in all the images of the multi-view dataset, allowing us to use the resulting model in our mixed IBR algorithm. Our results show significant improvement in image quality for free-viewpoint IBR, especially when moving far from the captured viewpoints.

关键词： Three-dimensional displays Solid modeling Rendering (computer graphics) Automobiles Databases Biological system modeling Cameras

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A Multicore Accelerated Implementation for Statistical Analysis of Facial Expressions in Video

A Multicore Accelerated Implementation for Statistical Analy...

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international Scientific and Technical conference on computer Science and Information Technologies

作者： Sumeyye Bayrakdar Ibrahim Yucedag Devrim Akgun Department of Computer Engineering Duzce University Department of Computer Engineering Sakarya University

ISBN: (纸本)9781509027415

Recently, the analysis of facial expressions has become one of the important research areas in computer vision and image processing. Analysing facial expressions quickly and accurately play a critical role in many software systems for various applications. In this study, a new algorithm is proposed for the acceleration of video-based facial expression analysis that is performed using cubic Bezier curves. Performance evaluation of the expression analysis accelerated with parallel threads on multi-core computers has been presented. The experiments have been conducted with eNTERFACE'05 emotion video database. Experimental results were obtained using quad-core processor with Hyper Threading technology. According to experimental results, quad core processor using two threads produced about 1.8 fold speed-up and four threads produced about 2.9 fold speed-up while eight threads produced about 3.5 fold speed-up has been obtained.

关键词： Cubic Bezier curves Facial expression analysis Multi-core acceleration Parallel programming

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Noise stable image registration using RANdom RESAmple Consensus

Noise stable image registration using RANdom RESAmple Consen...

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international conference on Pattern Recognition

作者： Atsushi Nakazawa Department of Informatics Kyoto University

ISBN: (纸本)9781509048489

image registration is an important and fundamental problem in computer vision and image processing. Although there are currently a large number of image registration algorithms such as RANSAC and its extensions, image registration under very noisy conditions remains difficult when it cannot obtain enough number of correct corresponding points. This paper solves this issue by introducing a random resample consensus (RANRESAC) strategy, which achieves robust registration where it is difficult to obtain enough numbers of correct correspondence pairs. In contrast to RANSAC, proposed RANRESAC newly generate corresponding points for the images using the hypothesis transformation function, and verifies the correctness by evaluating the similarity of the local features at the newly sampled points. To confirm the effectiveness for the proposed method, we first conducted an preliminary experiment that evaluates the similarity of texture and orientation components of SURF local descriptor in the images adding several levels of noise. As the result, we observed the texture component is more stable than the orientation component. Based on this finding, we design the RANRESAC algorithm and performed experiments using a open image registration dataset. As the result, proposed method outperforms to the RANSAC, MSAC and Optimal RANSAC algorithms in large noise conditions.

关键词： image registration Noise measurement Feature extraction Robustness Algorithm design and analysis Cameras

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Relaxation based multiple frame matching of an urban building with street view images

Relaxation based multiple frame matching of an urban buildin...

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international conference on Applied System Innovation (ICASI)

作者： Bumseok Cho Yong Cheol Kim Department of Electrical and Computer Engineering University of Seoul Dongdaemun Seoul Korea

ISBN: (纸本)9781467398893

We propose a multi-frame verification of relaxation based matching of clusters of SIFT keypoints. Mean shift clustering is performed to extract groups of SIFT keypoints which are homogeneous on location and orientation as well as gradient vectors. Relaxation based matching significantly enhances the reliability of correspondence, by preserving the structural consistency over matched clusters. The remnant false matches can be removed by verification by multi-frame verification. The consistency level of correspondence over multiple frames is used to distinguish false positives from true positives. Inter-frame homography is used to measure the deviation of the predicted matching vectors from the measured ones. Experiments on matching with Google street view images in San Francisco show that the proposed method achieves significant improvement when more than four consecutive frames are used for verification.

关键词： Pattern analysis Decision support systems computer vision Handheld computers IEEE conference proceedings Visual communication image processing

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Joint Semantic Segmentation and Depth Estimation with Deep Convolutional Networks

Joint Semantic Segmentation and Depth Estimation with Deep C...

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international conference on 3D Imaging, Modeling, processing, Visualization and Transmission (3DIMPVT)

作者： Arsalan Mousavian Hamed Pirsiavash Jana Košecká George Mason University Fairfax VA University of Maryland Baltimore County Baltimore MD

Multi-scale deep CNNs have been used successfully for problems mapping each pixel to a label, such as depth estimation and semantic segmentation. It has also been shown that such architectures are reusable and can be used for multiple tasks. These networks are typically trained independently for each task by varying the output layer(s) and training objective. In this work we present a new model for simultaneous depth estimation and semantic segmentation from a single RGB image. Our approach demonstrates the feasibility of training parts of the model for each task and then fine tuning the full, combined model on both tasks simultaneously using a single loss function. Furthermore we couple the deep CNN with fully connected CRF, which captures the contextual relationships and interactions between the semantic and depth cues improving the accuracy of the final results. The proposed model is trained and evaluated on NYUDepth V2 dataset [23] outperforming the state of the art methods on semantic segmentation and achieving comparable results on the task of depth estimation.

关键词： Semantics Estimation image segmentation Feature extraction Training Proposals computer architecture

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Poster Abstract: Efficient Visual Positioning with Adaptive Parameter Learning

Poster Abstract: Efficient Visual Positioning with Adaptive ...

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international Symposium on Information processing in Sensor Networks (IPSN)

作者： Hongkai Wen Sen Wang Ronnie Clark Savvas Papaioannou Niki Trigoni Department of Computer Science University of Oxford Oxford UK

Positioning with vision sensors is gaining its popularity, since it is more accurate, and requires much less bootstrapping and training effort. However, one of the major limitations of the existing solutions is the expensive visual processing pipeline: on resource-constrained mobile devices, it could take up to tens of seconds to process one frame. To address this, we propose a novel learning algorithm, which adaptively discovers the place dependent parameters for visual processing, such as which parts of the scene are more informative, and what kind of visual elements one would expect, as it is employed more and more by the users in a particular setting. With such meta- information, our positioning system dynamically adjust its behaviour, to localise the users with minimum effort. Preliminary results show that the proposed algorithm can reduce the cost on visual processing significantly, and achieve sub-metre positioning accuracy.

关键词： Visualization image resolution Pipelines Mobile handsets Feature extraction Vocabulary Sensors

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Affective Relationship between Color and Text in Arabic Comic Books

Affective Relationship between Color and Text in Arabic Comi...

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international IEEE conference on Signal-image Technologies and Internet-Based System

作者： Hadi S. Jomaa Mohamad Kamereddine Ammar Nayal Yara Rizk Mariette Awad Department of Electrical and Computer Engineering American University of Beirut Lebanon

Comic books are considered a heritage in many countries. The colorful depiction of annotated events has gained an increasing amount of interest over the past decade as the digitization process took over printed media, in addition to the abundance and variety of available data. Several applications have been devised in the field of computer vision and natural language processing to handle comic book pages. However, in this paper, we focus on the connection between the two, specifically, we compare the emotions that color and text separately imply. The theory of color and its effect on one's emotional state can be dated back to the 1800's. The language used in speech balloons is also written to a way to capture the audience's attention and manipulate their emotions. Throughout this paper, the color theory is applied to analyze the pages' emotional implication, and compared to the output of minSVM, a modified SVM classifier that accommodates imbalanced datasets, and a regular SVM, that are trained and implemented on the extracted text of a homegrown database to identify the emotions they convey. Using minSVM, we obtained a 91.26 % accuracy as opposed to an 89.66 % with SVM.

关键词： image color analysis Speech Shape Feature extraction Support vector machines Text categorization Databases

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Single image haze removal algorithm using pixel-based airlight constraints

Single image haze removal algorithm using pixel-based airlig...

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international conference on Automation and Computing (ICAC)

作者： Zhenwei Gao Yongqiang Bai Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China

Fast single image dehazing has been a challenging problem in many fields, such as computer vision and real-time applications. The existing image dehazing algorithms cannot achieve a trade-off between the dehazing performance and the computational complexity. The proposed approach first applies the mean filter twice to estimate airlight, which include pixel-based dark channel and bright channel constraints. And then the relationship between channel values of the restored image and atmospheric light is qualitatively analyzed to give the optimum estimate of atmospheric light. Using the airlight and atmospheric light, we can easily restore the scene radiance via the atmospheric scattering model. Compared with others, the main advantage of the proposed approach is its high speed and significant visibility improvement even in the sky and white areas. This speed allows the enhanced haze image to be applied in real-time processing applications. A comparative study and quantitative evaluation are proposed with a few other state of the art algorithms which demonstrates that similar or better quality results are obtained.

关键词： Atmospheric modeling image restoration Real-time systems Channel estimation Scattering Filtering Computational modeling

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Detection methods of new vessels in retinal fundus images — A survey

Detection methods of new vessels in retinal fundus images —...

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international conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE)

作者： S. Eswari S. Raja Rajeswari Department of computer science and Engineering Regional Campus Anna University Tirunelveli

ISBN: (纸本)9781467384384

Diabetic Retinopathy (DR) is a persistent disease which affects retinal blood vessels of diabetic patients leading to lack of vision. New blood vessels start appearing at the final stage of this disease termed as Proliferative Diabetic Retinopathy. There are many techniques that helps to diagnose DR and detection of new vessels in retinal fundus images. This paper reviews, classifies and compares each methods of various processing stages previously proposed in order to develop better and more effective methods for new vessel detection.

关键词： Feature extraction Blood vessels Biomedical imaging Retina Diabetes Retinopathy image segmentation

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Speed-adaptive ratio-based lane detection algorithm for self-driving vehicles

Speed-adaptive ratio-based lane detection algorithm for self...

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international SoC Design conference, ISOCC

作者： Seongrae Kim Junhee Lee Youngmin Kim Department of Computer Engineering Kwangwoon University Seoul Republic of Korea

ISBN: (纸本)9781509032204

Lane detection algorithm using a vision sensor or a camera would be more effective for self-driving vehicles to keep in lane, if it is possible to derive a distance ratio between a vehicle and left-right lanes. However, a dangerous situation may occur if the performance of the camera (e.g., frame/sec.) and the real-time speed of the vehicle are not considered properly because of the huge distance difference among frames for a fast moving vehicle with a low-speed camera. In this study, we propose a simple method to anticipate the relative position of the vehicle in the following frame from the current frame image. The expected ratio between a vehicle and the left-right lanes can be obtained by using of the speed of a vehicle and the frame speed of a camera. Experiment results show that less than 5.28% error occurs by the proposed algorithm for various cars and cameras.

关键词： Vehicles Cameras Mathematical model Detection algorithms image processing Control systems Real-time systems

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