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Combining attention and recognition for rapid scene analysis

Combining attention and recognition for rapid scene analysis

引用

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

作者： J.J. Bonaiuto L. Itti Neuroscience Department University of Southern California Los Angeles CA USA

Bottom-up visual attention allows primates to quickly select regions of an image that contain salient objects. In artificial systems, restricting the task of object recognition to these regions allows faster recognition and unsupervised learning of multiple objects in cluttered scenes. A problem is that objects superficially dissimilar to the target are given the same consideration in recognition as similar objects. Here we investigate rapid pruning of the recognition search space using the already-computed low-level features that guide attention. Itti and Koch’s bottom-up visual attention algorithm selects salient locations based on low-level features such as contrast, orientation, color, and intensity. Lowe’s SIFT recognition algorithm then extracts a signature of the attended object, for comparison with the object database. The database search is prioritized for objects which better match the low-level features used to guide attention to the current candidate for recognition. The SIFT signatures of prioritized database objects are then checked for match against the attended candidate. By comparing performance of Lowe’s recognition algorithm and Itti and Koch’s bottom-up attention model with or without search space pruning, we demonstrate that our pruning approach improves the speed of object recognition in complex natural scenes.

关键词： Image analysis Object recognition Layout Object oriented databases Spatial databases Visual databases Unsupervised learning Neuroscience Target recognition Object detection

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Dense 3D Reconstruction with an Uncalibrated Stereo System using Coded Structured Light

Dense 3D Reconstruction with an Uncalibrated Stereo System u...

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

作者： R. Furukawa H. Kawasaki Faculty of Information Sciences Hiroshima City University Hiroshima Japan Institute of Industrial Science Tokyo University Tokyo Japan

In this paper, we describe a new uncalibrated active vision system. Normally, active vision systems need either precise calibrations or relatively fixed cameras and light sources, which require 3D measurement systems to make use of complicated measurement processes or measurement equipment. Recently, several uncalibrated active vision systems have been studied. Since calibrations of these systems are done either while or after shape data is obtained, the user can simply place the equipment arbitrarily and scan the objects. The proposed system is an uncalibrated active vision system which consists of a camera and a video projector. Geometrically, this is a camera-to-camera system with one camera replaced by a projector. Uncalibrated vision systems based on perspective projection devices are prone to unmeasured scaling parameters. To solve this problem, a laser pointer is attached to the projector. In the present work, coded structured light is used to obtain dense correspondence points, resulting in more detailed shape representations. Experiments using the implemented system show that it is able to reconstruct dense and precise 3D shapes.

关键词： Stereo vision Machine vision Shape Calibration Cameras Optical control Control systems Image reconstruction Lighting control Servomechanisms

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Dense photometric stereo using a mirror sphere and graph cut

Dense photometric stereo using a mirror sphere and graph cut

引用

conference on computer vision and pattern recognition (cvpr)

作者： Tai-Pang Wu Chi-Keung Tang Vision and Graphics Group Hong Kong University of Science and Technology Hong Kong China

ISBN: (纸本)0769523722

We present a surprisingly simple system that performs robust normal reconstruction by dense photometric stereo, in the presence of large shadows, highlight, transparencies, complex geometry, variable attenuation in light intensity and inaccurate light directions. Our system consists of a mirror sphere, a spotlight and a DV camera only. Using this, we infer a dense set of unbiased but noisy photometric data uniformly distributed on the light direction sphere. We use this dense set to derive a very robust matching cost for our MRF photometric stereo model, where the maximum a posteriori (MAP) solution is estimated. To aggregate support for candidate normals in the normal refinement process, we introduce a compatibility function that is translated into a discontinuity-preserving metric, thus speeding up the MAP estimation by energy minimization using graph cut. No reference object of similar material is used. We perform detailed comparison on our approach with conventional convex minimization. We show very good normals estimated from very noisy data on a wide range of difficult objects to show the robustness and usefulness of our method.

关键词： Photometry Mirrors Robustness Stereo vision Geometry Cameras Reflectivity Surface contamination Surface reconstruction Surface texture

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Fast illumination-invariant background subtraction using two views: error analysis, sensor placement and applications

Fast illumination-invariant background subtraction using two...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Ser-Nam Lim A. Mittal L.S. Davis N. Paragios CS Department University of Maryland College Park USA Siemens Corporate Research Inc. Princeton NJ USA Ecole Nationale des Ponts et Chaussees France

Background modeling and subtraction to detect new or moving objects in a scene is an important component of many intelligent video applications. Compared to a single camera, the use of multiple cameras leads to better handling of shadows, specularities and illumination changes due to the utilization of geometric information. Although the result of stereo matching can be used as the feature for detection, it has been shown that the detection process can be made much faster by a simple subtraction of the intensities observed at stereo-generated conjugate pairs in the two views. The methodology however, suffers from false and missed detections due to some geometric considerations. In this paper, we perform a detailed analysis of such errors. Then, we propose a sensor configuration that eliminates false detections. Algorithms are also proposed that effectively eliminate most detection errors due to missed detections, specular reflections and objects being geometrically close to the background. Experiments on several scenes illustrate the utility and enhanced performance of the proposed approach compared to existing techniques.

关键词： Error analysis Object detection Cameras Lighting Layout Hardware Educational institutions computer vision Performance analysis Reflection

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Reliable solution for object pose determination using an active vision system

Reliable solution for object pose determination using an act...

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12th International conference on Advanced Robotics, 2005. ICAR '05

作者： Meng, Yan Zhuang, Hanqi Department of Electrical and Computer Engineering Stevens Institute of Technology Hoboken NJ 07010 United States Department of Electrical Engineering Florida Atlantic University Boca Raton FL 33431

ISBN: (纸本)0780391772

The problem of pose determination using a calibrated structured light system Is to determine the position and orientation of an object relative to a camera coordinate frame. By projecting a multiple-line light pattern to the three planes of the object, a number of line-to-plane correspondences can be obtained, from which an efficient and compact closed-form solution for the pose determination Is derived. The performance of the proposed algorithm In the presence of noise Is also Investigated. Preliminary experiments conducted with a structured light system shows that this novel method Is robust, efficient and Is applicable to the real-time pose determination of mobile robot. © 2005 ieee.

关键词： Gesture recognition

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Representational oriented component analysis (ROCA) for face recognition with one sample image per training class

Representational oriented component analysis (ROCA) for face...

引用

conference on computer vision and pattern recognition (cvpr)

作者： F. De la Torre R. Gross S. Baker B.V.K. Vijaya Kumar Robotics Institute Carnegie Mellon University Pittsburgh Pennsylvania Robotics Institute Carnegie Mellon University Pittsburgh Pennsylvania USA Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh Pennsylvania USA

Subspace methods such as PCA, LDA, ICA have become a standard tool to perform visual learning and recognition. In this paper we propose representational oriented component analysis (ROCA), an extension of OCA, to perform face recognition when just one sample per training class is available. Several novelties are introduced in order to improve generalization and efficiency: (1) combining several OCA classifiers based on different image representations of the unique training sample is shown to greatly improve the recognition performance. (2) To improve generalization and to account for small misregistration effect, a learned subspace is added to constrain the OCA solution, (3) a stable/efficient generalized eigenvector algorithm that solves the small size sample problem and avoids overfitting. Preliminary experiments in the FRGC Ver 1.0 dataset show that ROCA outperforms existing linear techniques (PCA, OCA) and some commercial systems.

关键词： Image analysis Face recognition Independent component analysis Samarium Principal component analysis Linear discriminant analysis Matched filters Image recognition Power system modeling Face detection

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Interactive montages of sprites for indexing and summarizing security video

Interactive montages of sprites for indexing and summarizing...

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conference on computer vision and pattern recognition (cvpr)

作者： C. Pal N. Jojic Department Computer Science University of Massachusetts Amherst MA USA Microsoft Research Limited Redmond WA USA

In this video we present a new model of interaction for indexing and visualizing video in the context of security applications. We present a method of indexing video by arranging irregularly shaped icons or sprites into a montage representing motion events or security events within the original video scene. The sprites in the montage are used as an index into the original video. We also generate video montages to summarize video in which motion events are compressed and overlayed in a video of shorter time duration. This summary video also acts as an index into the original video stream. We use a simple, novel method of extracting sprites for the image and video montages based on incrementally building a Gaussian mixture model with conjugate priors for the background. We then use fast morphological operators to extract foreground elements. Our approach can be viewed as a fast maximum a posteriori (MAP) inference procedure in a layered image model. The contributions of this work are new interaction and summary schemes that allow viewers to potentially survey hours of security video in the order of minutes.

关键词： Sprites (computer) Indexing Video compression Videoconference Layout Data security Pixel Surveillance Animation computer science

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Segmentation of edge preserving gradient vector flow: an approach toward automatically initializing and splitting of snakes

Segmentation of edge preserving gradient vector flow: an app...

引用

conference on computer vision and pattern recognition (cvpr)

作者： Chunming Li Jundong Liu M.D. Fox Department of Electrical and Computer Engineering University of Connecticut Storrs CT USA School of Electrical Engineering and Computer Science Ohio University Athens OH USA

Active contours or snakes have been extensively utilized in handling image segmentation and classification problems. In traditional active contour models, snake initialization is performed manually by users, and topological changes, such as splitting of the snake, can not be automatically handled. In this paper, we introduce a new method to solve the snake initialization and splitting problem, based on an area segmentation approach: the external force field is segmented first, and then the snake initialization and splitting can be automatically performed by using the segmented external force field. Such initialization and splitting produces multiple snakes, each of which is within the capture range associated to an object and evolved to the object boundary. The external force used in this paper is a gradient vector flow with an edge-preserving property (EPGVF), which can prevent the snakes from passing over weak boundaries. To segment the external force field, we represent it with a graph, and a graph-theory approach can be taken to determine the membership of each pixel. Experimental results establish the effectiveness of the proposed approach.

关键词： Active contours Solid modeling Topology Image segmentation computer science Computed tomography Spline Level set Active shape model Active noise reduction

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The shape analysis based on curve-structure moment invariants

The shape analysis based on curve-structure moment invariant...

引用

International conference on Neural Networks and Brain (ICNN&B 2005)

作者： Li, ZM Zhang, QL Hou, QP Diao, LH Li, H China Univ Petr Sch Comp Sci & Commun Engn Shandong 257061 Peoples R China

ISBN: (纸本)0780394224

Object shape comparability is a challenging problem in the field of pattern recognition and computer vision. The method based on the geometric moment invariants is the typical method in these applications. This paper introduces curve structure moment invariants based on the geometric moment invariants from transforming the density in geometric moments into a new density. The difference in the shapes is increased by using the curve structure moment invariants. Therefore, this method can be used in object shape analysis. To support our new theory, an algorithm for object shape analysis is designed and experiments based on square transform are conducted. Experiments give an encouraging high recognition rate by using the curve structure moment invariants.

关键词： Object recognition

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Object detection using 2D spatial ordering constraints

Object detection using 2D spatial ordering constraints

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conference on computer vision and pattern recognition (cvpr)

作者： Y. Li Y. Tsin Y. Genc T. Kanade ECE Department Carnegie Mellon University USA Real-time Vision and Modeling Siemens Corporate Research Inc. USA

Object detection is challenging partly due to the limited discriminative power of local feature descriptors. We amend this limitation by incorporating spatial constraints among neighboring features. We propose a two-step algorithm. First, a feature together with its spatial neighbors forms a flexible feature template. Two feature templates can be compared more informatively than two individual features without knowing the 3D object model. A large portion of false matches can be excluded after the first step. In a second global matching step, object detection is formulated as a graph-matching problem. A model graph is constructed by applying Delaunay triangulation on the surviving features. The best matching graph in an input image is computed by finding the maximum a posterior (MAP) estimate of a binary Markov random field with triangular maximal clique. The optimization is solved by the max-product algorithm (a.k.a. belief propagation). Experiments on both rigid and non-rigid objects demonstrate the generality and efficacy of the proposed methods.

关键词： Object detection computer vision Cameras Detectors Robot vision systems Signal resolution Spatial resolution Markov random fields Belief propagation Object recognition

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