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First steps towards stereo-based 6DOF SLAM for the visually impaired

First steps towards stereo-based 6DOF SLAM for the visually ...

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2005 IEEE computer Society conference on computer vision and pattern recognition, CVPR 2005 - workshops

作者： Sáez, Juan Manuel Escolano, Francisco Peñalver, Antonio Robot Vision Group Departamento de Ciencia de la Computación e Inteligencia Artificial Universidad de Alicante Ap.99 AlicanteE-03080 Spain

ISBN: (纸本)0769526608

In this work we have embodied a full 6DOF SLAM solution into a wearable stereo device working in near real-time. In order to serve on-line metric (map) and positional (localization) to the blind or visually impaired we introduce three basic elements: (i) a real-time egomotion estimation integrating 3D and 2D (appearance) information;(ii) a randomized algorithm for global rectification by entropy minimization;and (iii) a time-dependent view integration strategy for reducing the number of variables and achieving near real-time performance in global rectification. We show successful experimental results which illustrate the capabilities of both the egomotion and the global-rectification algorithm in terms of supporting 6DOF, yielding statistical robustness and enabling scalable solutions. © 2005 IEEE computer Society. All rights reserved.

关键词： Entropy

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On-vehicle and aerial texture analysis for vision-based desert road following

On-vehicle and aerial texture analysis for vision-based dese...

引用

2005 IEEE computer Society conference on computer vision and pattern recognition, CVPR 2005 - workshops

作者： Rasmussen, Christopher Korah, Thommen Department of Computer and Information Sciences University of Delaware United States

ISBN: (纸本)0769526608

We present two components of a vision-based approach to autonomous driving on and near rural and desert roads. The first component comprises fast processing of live vehicle camera video to robustly extract linear direction and midline estimates of marginal roads. The second uses satellite imagery immediately surrounding the vehicle's GPS position to trace the road ahead for curve and corner anticipation, and to inform the vehicle planner of a nearby road when traveling cross-country. The algorithms are built upon Gabor wavelet filters for texture analysis: on-board, they are employed to find ruts and tracks from which the road vanishing point can be inferred via Hough-style voting, and aerially, they localize the edges of low-contrast road contours. Mechanisms for both modules to determine whether the vehicle is currently on- or off-road are also explained. Our system's efficacy is illustrated for several difficult datasets, including a log from one vehicle's run during the 2004 DARPA Grand Challenge. © 2005 IEEE computer Society. All rights reserved.

关键词： Satellite imagery

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Adaptive rigid multi-region selection for handling expression variation in 3D face recognition

Adaptive rigid multi-region selection for handling expressio...

引用

2005 IEEE computer Society conference on computer vision and pattern recognition, CVPR 2005 - workshops

作者： Chang, Kyong I. Bowyer, Kevin W. Flynn, Patrick J. Computer Science and Engineering Department University of Notre Dame Notre DameIN46556 United States

ISBN: (纸本)0769526608

We present a new algorithm for 3D face recognition, and compare its performance to that of previous approaches. We focus especially on the case of facial expression change between gallery and probe images. We first establish performance comparisons using a PCA ("eigenface") algorithm and an ICP (iterative closest point) algorithm similar to ones reported in the literature. Experimental results show that the performance of either approach degrades substantially in the case Then we introduce a new algorithm, Adaptive Rigid Multi-region Selection, is introduced to independently matches multiple facial regions and creates a fused result. This algorithm is fully automated and used no manually selected landmark points. Experimental results show that our new algorithm substantially improves performance in the case of varying facial expression. Our experimental results are based on the largest 3D face dataset to date, with 449 persons, over 4,000 3D images, and substantial lapse between gallery and probe images. © 2005 IEEE computer Society. All rights reserved.

关键词： Probes

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Face identification by a cascade of rejection classifiers

Face identification by a cascade of rejection classifiers

引用

2005 IEEE computer Society conference on computer vision and pattern recognition, CVPR 2005 - workshops

作者： Yuan, Quan Thangali, Ashwin Sclaroff, Stan Computer Science Boston University BostonMA02215 United States

ISBN: (纸本)0769526608

Nearest neighbor search is commonly employed in face recognition but it does not scale well to large dataset sizes. A strategy to combine rejection classifiers into a cascade for face identification is proposed in this paper. A rejection classifier for a pair of classes is defined to reject at least one of the classes with high confidence. These rejection classifiers are able to share discriminants in feature space and at the same time have high confidence in the rejection decision. In the face identification problem, it is possible that a pair of known individual faces are very dissimilar. It is very unlikely that both of them are close to an unknown face in the feature space. Hence, only one of them needs to be considered. Using a cascade structure of rejection classifiers, the scope of nearest neighbor search can be reduced significantly. Experiments on Face recognition Grand Challenge (FRGC) version 1 data demonstrate that the proposed method achieves significant speed up and an accuracy comparable with the brute force Nearest Neighbor method. In addition, a graph cut based clustering technique is employed to demonstrate that the pairwise separability of these rejection classifiers is capable of semantic grouping. © 2005 IEEE computer Society. All rights reserved.

关键词： Nearest neighbor search

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Redundant class-dependence feature analysis based on correlation filters using FRGC2.0 data

Redundant class-dependence feature analysis based on correla...

引用

2005 IEEE computer Society conference on computer vision and pattern recognition, CVPR 2005 - workshops

作者： Xie, Chunyan Savvides, Marios Kumar, B.V.K. Vijaya Carnegie Mellon University Department of Electrical and Computer Engineering 5000 Forbes Avenue PittsburghPA15213 United States

ISBN: (纸本)0769526608

In this paper we propose a new method called redundant class-dependence feature analysis (CFA) based on the advanced correlation filters to perform robust face recognition on the Face recognition Grand Challenge (FRGC) data set. The FRGC contains a large corpus of data and a set of challenge problems. The data is divided into training and validation partitions, with the standard still-image training partition consisting of 12,800 images, and the validation partition consisting of 16,028 controlled still images, 8,014 uncontrolled stills, and 4,007 3D scans. We have tested the proposed CFA method and compared it with the PCA and LDA methods in a recognition scenario on the FRGC2.0 data. The preliminary results show that the CFA outperforms the other two compared methods in our experiments. We also show the improved performance of the CFA method on the FRGC experiments #1 and #4. © 2005 IEEE computer Society. All rights reserved.

关键词： Face recognition

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A visibility improvement system for low vision drivers by nonlinear enhancement of fused visible and infrared video

A visibility improvement system for low vision drivers by no...

引用

2005 IEEE computer Society conference on computer vision and pattern recognition, CVPR 2005 - workshops

作者： Ngo, Hau Tao, Li Zhang, Ming Livingston, Adam Asari, Vijayan Computational Intelligence and Machine Vision Laboratory Department of Electrical and Computer Engineering Old Dominion University NorfolkVA23529 United States

ISBN: (纸本)0769526608

Development of a visibility improvement system for helping drivers with poor vision during night and bad weather conditions is proposed in this paper. Video streams captured by a CCD camera and an infrared camera are registered and fused to obtain image details in extremely low lighting conditions. A novel image enhancement technique employing a nonlinear expansion function is developed for enhancing the fused images. The slope characteristics of the expansion function at an individual pixel location is based on the statistical properties of its neighborhood pixels. The expansion function is also capable of reducing the intensity of the overly bright image regions due to the presence of head lights from vehicles in opposite direction. The enhanced video stream is then subjected to a color restoration process to introduce natural color using the color information gathered from the CCD camera image. The entire image processing and analysis system is being installed in an FPGA environment for performing the processing in real-time. The processed video stream is displayed on a Head-Up Display located directly in front of the driver to assist him/her to drive safely in poor visibility environments. Preliminary results obtained in various experiments conducted with the proposed system are encouraging. © 2005 IEEE computer Society. All rights reserved.

关键词： CCD cameras

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3D face recognition using mapped depth images

3D face recognition using mapped depth images

引用

2005 IEEE computer Society conference on computer vision and pattern recognition, CVPR 2005 - workshops

作者： Pan, Gang Han, Shi Wu, Zhaohui Wang, Yueming Department of Computer Science Zhejiang University Hangzhou310027 China

ISBN: (纸本)0769526608

This paper addresses 3D face recognition from facial shape. Firstly, we present an effective method to automatically extract ROI of facial surface, which mainly depends on automatic detection of facial bilateral symmetry plane and localization of nose tip. Then we build a reference plane through the nose tip for calculating the relative depth values. Considering the non-rigid property of facial surface, the ROI is triangulated and parameterized into an isomorphic 2D planar circle, attempting to preserve the intrinsic geometric properties. At the same time the relative depth values are also mapped. Finally we perform eigenface on the mapped relative depth image. The entire scheme is insensitive to pose variance. The experiment using FRGC database v1.0 obtains the rank-1 identification score of 95%, which outperforms the result of the PCA base-line method by 4%, which demonstrates the effectiveness of our algorithm. © 2005 IEEE computer Society. All rights reserved.

关键词： Face recognition

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Structured light based depth edge detection for object shape recovery

Structured light based depth edge detection for object shape...

引用

2005 IEEE computer Society conference on computer vision and pattern recognition, CVPR 2005 - workshops

作者： Kim, Cheolhwon Park, Jiyoung Yi, Juneho Turk, Matthew School of Information and Communication Engineering Sungkyunkwan University Korea Biometrics Engineering Research Center Korea Republic of Computer Science Department University of California Santa Barbara CA93106 United States

ISBN: (纸本)0769526608

This research features a novel approach that efficiently detects depth edges in real world scenes. Depth edges play a very important role in many computer vision problems because they represent object contours. We strategically project structured light and exploit distortion of light pattern in the structured light image along depth discontinuities to reliably detect depth edges. Distortion along depth discontinuities may not occur or be large enough to detect depending on the distance from the camera or projector. For practical application of the proposed approach, we have presented methods that guarantee the occurrence of the distortion along depth discontinuities for a continuous range of object location. Experimental results show that the proposed method accurately detect depth edges of human hand and body shapes as well as general objects. © 2005 IEEE computer Society. All rights reserved.

关键词： Edge detection

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Fusion-based background-subtraction using contour saliency

Fusion-based background-subtraction using contour saliency

引用

2005 IEEE computer Society conference on computer vision and pattern recognition, CVPR 2005 - workshops

作者： Davis, James W. Sharma, Vinay Dept. of Computer Science and Engineering Ohio State University ColumbusOH43210 United States

ISBN: (纸本)0769526608

We present a new contour-based background-subtraction technique using thermal and visible imagery for persistent object detection in urban settings. Statistical background-subtraction in the thermal domain is used to identify the initial regions-of-interest. Color and intensity information are used within these areas to obtain the corresponding regions-of-interest in the visible domain. Within each region, input and background gradient information are combined to form a Contour Saliency Map. The binary contour fragments, obtained from corresponding Contour Saliency Maps, are then combined. An A* path-constrained search along watershed boundaries is used to complete and close any broken contour segments. Lastly, the contour image is flood-filled to produce silhouettes. Results of our approach are presented and compared against manually segmented data. © 2005 IEEE computer Society. All rights reserved.

关键词： Object detection

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Empirical evaluation of advanced ear biometrics

Empirical evaluation of advanced ear biometrics

引用

2005 IEEE computer Society conference on computer vision and pattern recognition, CVPR 2005 - workshops

作者： Yan, Ping Bowyer, Kevin W. Department of Computer Science and Engineering University of Notre DameIN46556 United States

ISBN: (纸本)0769526608

We present results of the largest experimental investigation of ear biometrics to date. Approaches considered include a PCA ("eigen-ear") approach with 2D intensity images, achieving 63.8% rank-one recognition;a PCA approach with range images, achieving 55.3%;Hausdorff matching of edge images from range images, achieving 67.5%;and ICP matching of the 3D data, achieving 98.7%. ICP based matching not only achieves the best performance, but also shows good scalability with size of dataset. The data set used represents over 300 persons, each with images acquired on at least two different dates. In addition, the ICP-based approach is further applied on an expanded data set of 404 subjects, and achieves 97.5% rank one recognition rate. In order to test the robustness and variability of ear biometrics, ear symmetry is also investigated. In our experiments around 90% of people's right ear and left ear are symmetric. © 2005 IEEE computer Society. All rights reserved.

关键词： Principal component analysis

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