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Tree Trunks as Landmarks for Outdoor vision SLAM

Tree Trunks as Landmarks for Outdoor Vision SLAM

引用

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

作者： D.C. Asmar J.S. Zelek S.M. Abdallah Systems Design Engineering University of Waterloo Waterloo ONT Canada Mechanical Engineering Department American University of Beirut Beirut Lebanon

Simultaneous Localization and Mapping (SLAM) of robots is the process of building a map of the robot milieu, while simultaneously localizing the robot inside that map. Cameras have been recently proposed, as a replacement for laser range finders, for the purpose of detecting and localizing landmarks around the navigating robot. vision SLAM is either Interest Point (IP) based, where landmarks are images saliencies, or object-based where real objects are used as landmarks. The contribution of this paper is two prong: first, it details an approach based on Perceptual Organization (PO) to detect and track trees in a sequence of images, thereby promoting the use of a camera as a viable exteroceptive sensor for object-based SLAM; second,it demonstrates the superiority of the suggested PO system over two appearance-based algorithms in segmenting trees from difficult settings. Experiments conducted on a database of 873 images containing approximately 2008 tree trunks, show that the proposed system correctly classifies trees at 81 % with a false positive rate of 30%.

关键词： Simultaneous localization and mapping Sensor systems Cameras Machine vision Navigation Global Positioning System Design engineering Systems engineering and theory Robot vision systems Robot sensing systems

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Automatic Video Annotation by Mining Speech Transcripts

Automatic Video Annotation by Mining Speech Transcripts

引用

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

作者： A. Velivelli T.S. Huang Department of Electrical and Computer Engineering Beckman Institute for Advanced Science and Technology University of Illinois Urbana-Champaign Urbana-Champaign IL USA

We describe a model for automatic prediction of text annotations for video data. The speech transcripts of videos, are clustered using an aspect model and keywords are extracted based on aspect distribution. Thus we capture the semantic information available in the video data. This technique for automatic keyword vocabulary construction makes the labelling of video data a very easy task. We then build a video shot vocabulary by utilizing both static images and motion cues. We use a maximum entropy criterion to learn the conditional exponential model by defining constraint features over the shot vocabulary, keyword vocabulary combinations. Our method uses a maximum a posteriori estimate of exponential model to predict the annotations. We evaluate the ability of our model to predict annotations, in terms of mean negative log-likelihood and retrieval performance on the test set. A comparison of exponential model with baseline methods indicates that the results are encouraging.

关键词： Speech Predictive models Vocabulary Data mining Information retrieval Testing Content based retrieval Streaming media Labeling Entropy

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3D Surveillance A Distributed Network of Smart Cameras for Real-Time Tracking and its Visualization in 3D

3D Surveillance A Distributed Network of Smart Cameras for R...

引用

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

作者： S. Fleck F. Busch P. Biber W. Straber WSI/GRIS University of Tübingen Tübingen Germany

The demand for surveillance systems has increased extremely over recent times. We present a system consisting of a distributed network of cameras that allows for tracking and handover of multiple persons in real time. The intercamera tracking results are embedded as live textures in an integrated 3D world model which is available ubiquitously and can be viewed from arbitrary perspectives independent of the persons’ movements. We mainly concentrate on our implementation of embedded camera nodes in the form of smart cameras and discuss the benefits of such a distributed surveillance network compared to a host centralized approach. We also briefly describe our way of hassle free 3D model acquisition to cover the complete system from setup to operation and finally show some results of both an indoor and an outdoor system in operation.

关键词： Surveillance Smart cameras Visualization Intelligent networks Switches Real time systems Tracking Streaming media computer displays Security

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Privacy & Security Issues Related to Match Scores

Privacy & Security Issues Related to Match Scores

引用

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

作者： P. Mohanty S. Sarkar R. Kasturi Computer Science and Engineering University of South Florida Tampa FL USA

Security and privacy issues remains a major hurdle in wide deployment of biometric based authentication system. For example, unauthorized access or regeneration of face templates has serious implications on the privacy of the concerned users. For robust and practical implementation of such system it is necessary to identify and explore the possible ways by which reconstruction of template is feasible. In this paper, we show that even match scores carries sufficient information for reconstruction of the original face templates. We propose a novel non-iterative scheme to reconstruct face templates from match scores. We use an affine transformation of the images to approximate the behavior of a given face recognition system using an independent set of face templates termed as "break-in" set. Selected templates from the break-in set are matched only once with the enrolled template of the target account and match scores are recorded. These scores are then embedded in the approximating affine space along with break-in set templates to compute the co-ordinates of the target template. The inverse transformation is used to reconstruct the original target template. We present the reconstruction of templates for a commercial off the shelf (COTS) face recognition system. The COTS system is set to operate at 1% False Acceptance Rate and 99% True Acceptance Rate with 100 enrollments. We observed that with proposed scheme, at most 450 attempts are required to achieve a 0.93 probability of break into the COTS face recognition system by choosing a random gallery target.

关键词： Privacy Biometrics Image reconstruction Authentication Robustness Face recognition computer science computer security Embedded computing Availability

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New Validation Method for Establishing Correspondence Between Pairs of X-Ray Mammograms

New Validation Method for Establishing Correspondence Betwee...

引用

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

作者： J.H. Hipwell C. Tanner W.R. Crum D.J. Hawkes Centre for Medical Image Computing University College London London UK

Establishing spatial correspondence between features visible in x-ray mammograms obtained at different times has great potential to aid assessment of change in the breast indicative of malignant changes and facilitate their quantification. The literature contains numerous non-rigid registration algorithms developed for this purpose, but quantitative estimation of registration accuracy is limited. In this paper we describe a novel validation method which simulates plausible mammographic compressions of the breast using an MRI derived finite element model. By projecting the resulting known 3D displacements into 2D and simulating x-ray mammograms from these same compressed MR volumes, we can generate convincing images with known 2D displacements with which to validate a registration algorithm. We illustrate this approach by computing the accuracy for a non-rigid registration algorithm applied to mammographic test images generated from three patient MR datasets.

关键词： X-ray imaging Image coding Lesions Image generation Testing Breast cancer Magnetic resonance imaging Finite element methods Diseases computer vision

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Robust Fragments-based Tracking using the Integral Histogram

Robust Fragments-based Tracking using the Integral Histogram

引用

conference on computer vision and pattern recognition (CVPR)

作者： A. Adam E. Rivlin I. Shimshoni Department of Computer Science Technion-Israel Institute of Technology Haifa Israel Department of Management Information Systems Haifa University Haifa Israel

We present a novel algorithm (which we call "Frag- Track") for tracking an object in a video sequence. The template object is represented by multiple image fragments or patches. The patches are arbitrary and are not based on an object model (in contrast with traditional use of modelbased parts e.g. limbs and torso in human tracking). Every patch votes on the possible positions and scales of the object in the current frame, by comparing its histogram with the corresponding image patch histogram. We then minimize a robust statistic in order to combine the vote maps of the multiple patches. A key tool enabling the application of our algorithm to tracking is the integral histogram data structure [18]. Its use allows to extract histograms of multiple rectangular regions in the image in a very efficient manner. Our algorithm overcomes several difficulties which cannot be handled by traditional histogram-based algorithms [8, 6]. First, by robustly combining multiple patch votes, we are able to handle partial occlusions or pose change. Second, the geometric relations between the template patches allow us to take into account the spatial distribution of the pixel intensities - information which is lost in traditional histogram-based algorithms. Third, as noted by [18], tracking large targets has the same computational cost as tracking small targets. We present extensive experimental results on challenging sequences, which demonstrate the robust tracking achieved by our algorithm (even with the use of only gray-scale (noncolor) information).

关键词： Robustness Histograms Voting Target tracking Video sequences Torso Humans Statistics Data structures Data mining

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3D Target Scale Estimation and Motion Segmentation for Size Preserving Tracking in PTZ Video

3D Target Scale Estimation and Motion Segmentation for Size ...

引用

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

作者： Yi Yao B. Abidi M. Abidi Imaging Robotics and Intelligent Systems (IRIS) Laboratory University of Tennessee Knoxville TN USA

In size preserving video tracking, the camera’s focal length (zoom) is adjusted automatically to compensate for the changes in the target’s image size caused by the relative motion between the camera and the target. The accurate estimation of these changes is paramount to the system performance. The existing method of choice for real-time target scale estimation applies structure from motion (SFM) based on the weak perspective projection model [1]. We design a target scale estimation algorithm with linear solution based on the more advanced paraperspective projection model. Another key problem in SFM based algorithms is the separation between foreground and background features (image corners), especially when composite camera and target motions are involved. This paper also addresses a fast foreground/background separation algorithm, the affine shape method. The resulting segmentation automatically adapts to the target’s 3D geometry and motion. Experimental results illustrate the effectiveness of the proposed scale estimation and segmentation algorithms in tracking translating and rotating objects with a PTZ camera while preserving their sizes.

关键词： Motion estimation Motion segmentation computer vision Target tracking Cameras Image segmentation System performance Algorithm design and analysis Shape Geometry

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Integrating Co-Occurrence and Spatial Contexts on PatchBased Scene Segmentation

Integrating Co-Occurrence and Spatial Contexts on PatchBased...

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

作者： F. Monay P. Quelhas J.-M. Odobez D. Gatica-Perez Ecole Polytechnique Federale de Lausanne (EPFL) IDIAP Research Institute Martigny Switzerland

We present a novel approach for contextual segmentation of complex visual scenes, based on the use of bags of local invariant features (visterms) and probabilistic aspect models. Our approach uses context in two ways: (1) by using the fact that specific learned aspects correlate with the semantic classes, which resolves some cases of visual polysemy, and (2) by formalizing the notion that scene context is image-specific -what an individual visterm represents depends on what the rest of the visterms in the same bag represent too-. We demonstrate the validity of our approach on a man-made vs. natural visterm classification problem. Experiments on an image collection of complex scenes show that the approach improves region discrimination, producing satisfactory results, and outperforming a non-contextual method. Furthermore, through the later use of a Markov Random Field model, we also show that co-occurrence and spatial contextual information can be conveniently integrated for improved visterm classification.

关键词： Layout Context modeling Image segmentation Markov random fields computer vision Image resolution Indexing Image retrieval Image analysis Pixel

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Example Based 3D Reconstruction from Single 2D Images

Example Based 3D Reconstruction from Single 2D Images

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

作者： T. Hassner R. Basri Weizmann Institute of Science Rehovot Israel

We present a novel solution to the problem of depth reconstruction from a single image. Single view 3D reconstruction is an ill-posed problem. We address this problem by using an example-based synthesis approach. Our method uses a database of objects from a single class (e.g. hands, human figures) containing example patches of feasible mappings from the appearance to the depth of each object. Given an image of a novel object, we combine the known depths of patches from similar objects to produce a plausible depth estimate. This is achieved by optimizing a global target function representing the likelihood of the candidate depth. We demonstrate how the variability of 3D shapes and their poses can be handled by updating the example database on-the-fly. In addition, we show how we can employ our method for the novel task of recovering an estimate for the occluded backside of the imaged objects. Finally, we present results on a variety of object classes and a range of imaging conditions.

关键词： Image reconstruction Shape Image databases Humans Marine animals Rendering (computer graphics) pattern matching Graphical models Batteries Degradation

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When Occlusions are Outliers

When Occlusions are Outliers

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

作者： S. Goldenstein C. Vogler Instituto de Computação Universidade Estadual de Campinas (UNICAMP) Brazil Gallaudet Research Institute Gallaudet University USA

In many tracking applications, the deformable object of interest suffers from frequent occlusions. Traditional augmenting methods use templates and measures of similarity to recover from occlusions. In this paper, we break with these methods. Instead, we model bad image correspondences, which are induced by occlusions, as statistical outliers in the context of tracking high-dimensional deformable models. This interpretation allows us to use robust statistical estimators in the deformable model’s parameter space to detect and eliminate such outliers. Because fast-moving occlusions can generate an excessively large outlier to inlier ratio in the occluded areas, we combine the robust statistical estimation with an initial rejection of correspondences based on the magnitude of the optical flow, a simple 2D criterion. To improve robustness even further, we have the final outlier rejection test take into account both the statistical distribution of the deformable model’s parameters, and that different parameters are affected by different subsets of correspondences. We validate and demonstrate our technique on real sequences of American Sign Language, which exhibit frequent and extensive occlusions caused by fast movement of the subjects’ hands.

关键词： Deformable models Robustness Handicapped aids Context modeling computer vision Application software Image motion analysis Testing Statistical distributions Cognition

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