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Reconstruction of specular surfaces using polarization imaging

Reconstruction of specular surfaces using polarization imagi...

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conference on computer Vision and pattern recognition (CVPR)

作者： S. Rahmann N. Canterakis Institute for Pattern Recognition and Image Processing Computer Science Department University of Freiburg Freiburg im Breisgau Germany

ISBN: (纸本)0769512720

Traditional intensity imaging does not offer a general approach for the perception of textureless and specular reflecting surfaces. Intensity based methods for shape reconstruction of specular surfaces rely on virtual (i.e. mirrored) features moving over the surface under viewer motion. We present a novel method based on polarization imaging for shape recovery of specular surfaces. This method overcomes the limitations of the intensity based approach because no virtual features are required. It recovers whole surface patches and not only single curves on the surface. The presented solution is general as it is independent of the illumination. The polarization image encodes the projection of the surface normals onto the image and therefore provides constraints on the surface geometry. Taking polarization images from multiple views produces enough constraints to infer the complete surface shape. The reconstruction problem is solved by an optimization scheme where the surface geometry is modelled by a set of hierarchical basis functions. The optimization algorithm proves to be well converging, accurate and noise resistant. The work is substantiated by experiments on synthetic and real data.

关键词： image reconstruction Surface reconstruction Polarization Shape Geometry Surface texture Lighting Solid modeling image converters Multi-stage noise shaping

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Visual hull alignment and refinement across time: a 3D reconstruction algorithm combining shape-from-silhouette with stereo

Visual hull alignment and refinement across time: a 3D recon...

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conference on computer Vision and pattern recognition (CVPR)

作者： G.K.M. Cheung S. Baker T. Kanade Robotics Institute Carnegie Mellon University Pittsburgh PA USA

Visual hull (VH) construction from silhouette images is a popular method of shape estimation. The method, also known as shape-from-silhouette (SFS), is used in many applications such as non-invasive 3D model acquisition, obstacle avoidance, and more recently human motion tracking and analysis. One of the limitations of SFS, however, is that the approximated shape can be very coarse when there are only a few cameras. In this paper, we propose an algorithm to improve the shape approximation by combining multiple silhouette images captured across time. The improvement is achieved by first estimating the rigid motion between the visual hulls formed at different time instants (visual hull alignment) and then combining them (visual hull refinement) to get a tighter bound on the object's shape. Our algorithm first constructs a representation of the VHs called the bounding edge representation. Utilizing a fundamental property of visual hulls, which states that each bounding edge must touch the object at at least one point, we use multi-view stereo to extract points called colored surface points (CSP) on the surface of the object. These CSPs are then used in a 3D image alignment algorithm to find the 6 DOF rigid motion between two visual hulls. Once the rigid motion across time is known, all of the silhouette images are treated as being captured at the same time instant and the shape of the object is refined. We validate our algorithm on both synthetic and real data and compare it with space carving.

关键词： Reconstruction algorithms Shape Surface treatment Stereo image processing Humans Motion analysis Tracking image motion analysis Cameras Approximation algorithms

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Automatic input of flow chart in document image 82

Automatic input of flow chart in document image

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proceedings of the 6th international conference on Software engineering

作者： S. Ito

The technology of document image processing.has the possibility of automatic document input. By utilizing it, the flow chart in document image as the alternate expression of FORTRAN source statements is automatically input into the computer. The paper reports the algorithm and the experimental results of field segmentation and classification in document image, the recognition of flow chart including control lines and blocks, and hand-written alpha-numerical characters in the blocks and the explanatory fields, the conversion of flow chart into program functions and the generation of FORTRAN source statements. It showed the possibility that program functions such as initialization, input/output format and branch address were determined by the analysis of flow chart and explanatory description under the writing rule of it and also the restriction that the flow chart should have the good quality in order to recognize the flow and characters and be subject to the writing rule.

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Automated segmentation of iris images using visible wavelength face images

Automated segmentation of iris images using visible waveleng...

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ieee computer society conference on computer Vision and pattern recognition Workshops (CVPRW)

作者： Chun-Wei Tan Ajay Kumar Department of Computing Hong Kong Polytechnic University Hong Kong China

Remote human identification using iris biometrics requires the development of automated algorithm of the robust segmentation of iris region pixels from visible face images. This paper presents a new automated iris segmentation framework for iris images acquired at-a-distance using visible imaging. The proposed approach achieves the segmentation of iris region pixels in two stages, i.e. (i) iris and sclera classification, and (ii) post-classification processing. Unlike the traditional edge-based segmentation approaches, the proposed approach simultaneously exploits the discriminative color features and localized Zernike moments to perform pixel-based classification. Rigorous experimental results presented in this paper confirm the usefulness of the proposed approach and achieve improvement of 42.4% in the average segmentation errors, on UBIRIS.v2 dataset, as compared to the previous approach.

关键词： Iris Iris recognition image segmentation Feature extraction Lighting Training image color analysis

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A fast approach to hyperspectral band selection based on time series analysis

A fast approach to hyperspectral band selection based on tim...

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Chinese conference on pattern recognition

作者： Yu, Yufeng Yang, Jinhua Li, Shijin School of Computer and Information Hohai University Nanjing 210098 China

ISBN: (纸本)9781424472109

Hyperspectral remote sensing image has the characteristics of hundreds of bands, high relevancy, and high redundancy, which bring difficulties to the further processing.task. In order to reduce the dimension, this paper proposes an effective band selection method based on time series analysis of important points. The method takes all the continuous band of hyperspectral remote sensing images as time series and performs K-means clustering based on the DBI criterion firstly, then the cluster centers undergo wavelet filtering, and finally important points of the time series curves are extracted and merged as the basis for band selection. To verify the effectiveness of the proposed method, classification using SVM classifier is conducted on the reduced spectral images. The results show that the proposed band selection methods with important points based on time series analysis can choose those bands with discriminative information, and it can achieve dimension reduction rate close to 90%. Compared with other state-of-the-art methods, the presented method is competitive with a lower computational complexity, while maintaining a higher classification accuracy at the same time. ©2010 ieee.

关键词： Wavelet analysis

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A model-based road sign identification system

A model-based road sign identification system

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conference on computer Vision and pattern recognition (CVPR)

作者： Y.B. Lauziere D. Gingras F.P. Ferrie Centre for Intelligent Machines CIM McGill University Montreal QUE Canada INO Sainte-Foy QUE Canada Institute des Matériaux et Systèmes Intelligents IMSI Université de Sherbrook Sherbrooke QUE Canada

ISBN: (纸本)0769512720

A road sign (RS) recognition system poses a real challenge for machine vision. It must recognize a wide variety of RSs under considerable variations in illumination and imaging geometry-all in real-time. Such a system is presented, with emphasis on the system architecture and specific model-based techniques used in the different processing.steps. Central to this are a unique physics-based color detection approach and a novel template matching scheme for planar objects. Since the approach strongly relies on modelling for both detection and recognition, it offers the advantage of being reconfigurable by changing only a few parameters. The system is modular with respect to the sensor and the recognition data structure is simple to extend and maintain, and is easily adaptable to different regulations, e.g. North American vs European RSs. The data needed for recognition is computed automatically by modelling image formation with a few geometrical parameters. Experimental results are presented which demonstrate the performance of the system in a real task environment with high overall performance.

关键词： image recognition Roads Lighting Solid modeling image databases Spatial databases Geometry Machine intelligence Machine vision Object detection

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Handling occlusions in dense multi-view stereo

Handling occlusions in dense multi-view stereo

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conference on computer Vision and pattern recognition (CVPR)

作者： Sing Bing Kang R. Szeliski Jinxiang Chai Microsoft Research Microsoft Corporation USA The Robotics Institute Carnegie Mellon University USA

ISBN: (纸本)0769512720

While stereo matching was originally formulated as the recovery of 3D shape from a pair of images, it is now generally recognized that using more than two images can dramatically improve the quality of the reconstruction. Unfortunately, as more images are added, the prevalence of semi-occluded regions (pixels visible in some but not all images) also increases. We propose some novel techniques to deal with this problem. Our first idea is to use a combination of shiftable windows and a dynamically selected subset of the neighboring images to do the matches. Our second idea is to explicitly label occluded pixels within a global energy minimization framework, and to reason about visibility within this framework so that only truly visible pixels are matched. Experimental results show a dramatic improvement using the first idea over conventional multibaseline stereo, especially when used in conjunction with a global energy minimization technique. These results also show that explicit occlusion labeling and visibility reasoning do help, but not significantly, if the spatial and temporal selection is applied first.

关键词： Stereo vision Pixel Robots Stereo image processing Shape image reconstruction image recognition Labeling computer vision Application software

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Clustering art

Clustering art

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conference on computer Vision and pattern recognition (CVPR)

作者： K. Barnard P. Duygulu D. Forsyth Computer Division University of California Berkeley USA

ISBN: (纸本)0769512720

We extend a recently developed method (K. Barnard and D. Forsyth, 2001) for learning the semantics of image databases using text and pictures. We incorporate statistical natural language processing.in order to deal with free text. We demonstrate the current system on a difficult dataset, namely 10000 images of work from the Fine Arts Museum of San Francisco. The images include line drawings, paintings, and pictures of sculpture and ceramics. Many of the images have associated free text which varies greatly from physical description to interpretation and mood. We use WordNet to provide semantic grouping information and to help disambiguate word senses, as well as emphasize the hierarchical nature of semantic relationships. This allows us to impose a natural structure on the image collection that reflects semantics to a considerable degree. Our method produces a joint probability distribution for words and picture elements. We demonstrate that this distribution can be used: (a) to provide illustrations for given captions, and (b) to generate words for images outside the training set. Results from this annotation process yield a quantitative study of our method. Finally, the annotation process can be seen as a form of object recognizer that has been learned through a partially supervised process.

关键词： Subspace constraints image databases Predictive models Natural language processing Art Painting Ceramics Mood Probability distribution image generation

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3D head tracking using motion adaptive texture-mapping

3D head tracking using motion adaptive texture-mapping

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conference on computer Vision and pattern recognition (CVPR)

作者： L.M. Brown IBM Thomas J. Watson Research Center Hawthorne NY USA

ISBN: (纸本)0769512720

We have developed a fast robust 3D head tracking system based on rendering a texture-mapped cylinder. In order to handle the variable frame-to-frame motion changes, the system uses motion templates, which adapt to the current size of the motion increment. The relationship between measurable pixel energy and tracking error is used to design the parameters of the adaptive algorithm. To speedup processing.and decouple rotational and translational motion, 2D positional information of the neckline is utilize. The confidence at each point is computed based on the amount of information used in creating the texture map and re-rendering the face. The system can also handle large out-of-plane rotations via additional templates. If the tracker fails, it can recover using an independent face detection routine. We compare the results of our approach with the extensive results of a closely related technique.

关键词： Face recognition Head Humans image databases Robustness Face detection Facial animation Testing Energy measurement Algorithm design and analysis

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Removing weather effects from monochrome images

Removing weather effects from monochrome images

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conference on computer Vision and pattern recognition (CVPR)

作者： S.G. Narasimhan S.K. Nayar Department of Computer Sciences Columbia University NY USA

ISBN: (纸本)0769512720

images of outdoor scenes captured in bad weather suffer from poor contrast. Under bad weather conditions, the light reaching a camera is severely scattered by the atmosphere. The resulting decay in contrast varies across the scene and is exponential in the depths of scene points. Therefore, traditional space invariant image processing.techniques are not sufficient to remove weather effects from images. In this paper, we present a fast physics-based method to compute scene structure and hence restore contrast of the scene from two or more images taken in bad weather In contrast to previous techniques, our method does not require any a priori weather-specific or scene information, and is effective under a wide range of weather conditions including haze, mist, fog and other aerosols. Further, our method can be applied to gray-scale, RGB color, multi-spectral and even IR images. We also extend the technique to restore contrast of scenes with moving objects, captured using a video camera.

关键词： Layout image restoration Atmospheric modeling Light scattering Weather forecasting Cameras Aerosols Filtering Physics Atmospheric waves

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