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Word Channel Based Multiscale Pedestrian Detection Without image Resizing and Using Only One Classifier

Word Channel Based Multiscale Pedestrian Detection Without I...

引用

IEEE Conference on computer Vision and pattern recognition

作者： Arthur Daniel Costea Sergiu Nedevschi Image Processing and Pattern Recognition Group Computer Science Department Technical University of Cluj-Napoca

ISBN: (纸本)9781479951192

Most pedestrian detection approaches that achieve high accuracy and precision rate and that can be used for real-time applications are based on histograms of gradient orientations. Usually multiscale detection is attained by resizing the image several times and by recomputing the image features or using multiple classifiers for different scales. In this paper we present a pedestrian detection approach that uses the same classifier for all pedestrian scales based on image features computed for a single scale. We go beyond the low level pixel-wise gradient orientation bins and use higher level visual words organized into Word Channels. Boosting is used to learn classification features from the integral Word Channels. The proposed approach is evaluated on multiple datasets and achieves outstanding results on the INRIA and Caltech-USA benchmarks. By using a GPU implementation we achieve a classification rate of over 10 million bounding boxes per second and a 16 FPS rate for multiscale detection in a 640×480 image.

关键词： Visualization Boosting Training Feature extraction Graphics processing units Semantics image color analysis

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CAD-based computer vision: from CAD models to relational graphs

CAD-based computer vision: from CAD models to relational gra...

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IEEE International Conference on Systems, Man and Cybernetics

作者： P.J. Flynn A.K. Jain Pattern Recognition and Image Processing Laboratory Department of Computer Science Michigan State University East Lansing MI USA

The authors outline their approach for automatic translation of geometric entities produced by a CAD system into a relational graph structure. They have developed a system which uses 3-D object descriptions created on a commercial CAD system and expressed in the industry-standard IGES form, and performs geometric inferencing to object a relational graph representation of the object which can be stored in a database of models of object recognition. Details of the IGES standard, the geometric inference engine, and some formal properties of 3-D models are discussed. In addition to the process of translation from one data format to another, the interference engine extracts higher-level information from the CAD model and stores it explicitly in the new data structure. The higher-level features will allow the search space explored during the object recognition stage to be pruned early.< >

关键词： computer vision Solid modeling Object recognition Engines Space exploration Industrial relations Relational databases Spatial databases Interference Data mining

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Page segmentation using texture discrimination masks

Page segmentation using texture discrimination masks

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IEEE International Conference on image processing

作者： A.K. Jain Y. Zhong Pattern Recognition and Image Processing Laboratory Department of Computer Science Michigan State University East Lansing MI USA

We propose a new texture-based page segmentation algorithm which automatically extracts the text, halftone, and line-drawing regions from input greyscale document images. This approach utilizes a neural network to train a set of masks which is optimal for discriminating the three main texture classes in the page segmentation problem: halftone, background, and text and line-drawing regions. The test and line-drawing regions are further discriminated based on connectivity analysis. We have applied the algorithm to successfully segment English and Chinese document images. We also demonstrate that the masks can perform language separation (English/Chinese) when appropriately trained.

关键词： image segmentation Neural networks Gabor filters Natural languages image analysis Multi-layer neural network image texture analysis pattern recognition image processing Laboratories

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On-line fingerprint verification

On-line fingerprint verification

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International Conference on pattern recognition

作者： A. Jain Lin Hong Pattern Recognition and Image Processing Laboratory Department of Computer Science Michigan State University East Lansing MI USA

We describe the design and implementation of an online fingerprint verification system which operates in two stages: (i) minutia extraction and (ii) minutia matching. An improved minutia extraction algorithm that is much faster and more accurate than our earlier algorithm has been implemented. For minutia matching, an alignment-based elastic matching algorithm has been developed. This algorithm is capable of finding the correspondences between input minutiae and the stored template without resorting to exhaustive search and has the ability to adaptively compensate for the nonlinear deformations and inexact pose transformations between finger prints. The system has been tested on two sets of finger print images captured with inkless scanners. The verification accuracy is found to be over 99% with a 15% reject rate. Typically, a complete fingerprint verification procedure takes, on an average, about 8 seconds on a SPARC 20 workstation. It meets the response time requirements of on-line verification with high accuracy.

关键词： Fingerprint recognition Access control Feature extraction Flowcharts pattern recognition image processing Laboratories computer science pattern matching System testing

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A Modified Numerical Integration Method for Deformable Object Animation

A Modified Numerical Integration Method for Deformable Objec...

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Asia Simulation Conference 2007, AsiaSim 2007

作者： Hu, Xinrong Wei, Lan Li, Dehua Dept. of Computer Science and Technology WuHan University of Science and Engineering WuHan 430074 China Institute for Pattern Recognition and Artificial Intelligence State Education Commission Laboratory for Image Processing and Intelligence Control HuaZhong Univ. of Science and Technology WuHan 430074 China

ISBN: (纸本)9783540775997

A satisfied deformable object simulation should be general, accurate, efficient and stable. Explicit, implicit and semi-implicit numerical integration methods have contributed to large performance enhancements in the field of deformable simulation. Cloth is the most representative deformable object. In this paper, we propose an improved embedded Runge-Kutta integration method to solve the deformable simulation that based on classical spring-mass model. Traditional embedded Runge-Kutta methods generally solve ordinary differential equations of deformable object simulation. Most of them tend to concentrate on the efficiency of the simulation process, and not the fidelity of the simulation result. We investigate and determine the extent to which the overall quality must be compromised in order for the stable conditions to be satisfied. The improved Runge-Kutta method proposed in our paper incorporates the fixed time step and adaptive time step in solving cloth motion equations to achieve a controllable error evaluation. Compared with the other Runge-Kutta methods, the proposed method has some advantages for cloth simulation: controllable error evaluation without extra computations, excellent efficiency, good stability and satisfied precision. Experiment demonstrates that this method results in simulation efficiency improvements and is considerable practicable. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Animation

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Invariant grey-scale features for 3D sensor-data

Invariant grey-scale features for 3D sensor-data

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International Conference on pattern recognition

作者： M. Schael S. Siggelkow Institute for Pattern Recognition and Image Processing Computer Science Department University of Freiburg Freiberg Germany

ISBN: (纸本)0769507506

A technique for the construction of invariant features of 3D sensor-data is proposed. Invariant grey-scale features are characteristics of grey-scale sensor-data which remain constant if the sensor-data is transformed according to the action of a transformation group. The proposed features are capable of recognizing 3D objects independent of their orientation and position, which can be used e.g. in medical image analysis. The computation of the proposed invariants needs no preprocessing like filtering, segmentation, or registration. After the introduction of the general theory for the construction of invariant features for 3D sensor-data, the paper focuses on the special case of 3D Euclidean motion which is typical for rigid 3D objects. Due to the fact that we use the function of local support the calculated invariants are also robust with respect to independent Euclidean motion, articulated objects, and even topological deformations. The complexity of the method is linear in the data-set size which may be too high for large 3D objects. Therefore approaches for the acceleration of the computation are given. First experimental results for artificial 3D objects are presented in the paper to demonstrate the invariant properties of the proposed features.

关键词： Geometry pattern recognition Biomedical imaging Robustness image processing computer science image recognition image motion analysis Lubricating oils image segmentation

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Personal verification using palmprint and hand geometry biometric

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4th International Conference on Audio and Video-Based Biometric Person Authentication, AVBPA 2003

作者： Kumar, Ajay Wong, David C. M. Shen, Helen C. Jain, Anil K. Department of Computer Science Hong Kong University of Science and Technology Clear Water Bay Hong Kong Pattern Recognition and Image Processing Lab Department of Computer Science and Engineering Michigan State University East LansingMI48824 United States

ISBN: (纸本)9783540403029

A new approach for the personal identification using hand images is presented. This paper attempts to improve the performance of palmprint-based verification system by integrating hand geometry features. Unlike other bimodal biometric systems, the users does not have to undergo the inconvenience of passing through two sensors since the palmprint and hand geometry features can be are acquired from the same image, using a digital camera, at the same time. Each of these gray level images are aligned and then used to extract palmprint and hand geometry features. These features are then examined for their individual and combined performance. The image acquisition setup used in this work was inherently simple and it does not employ any special illumination nor does it use any pegs to cause any inconvenience to the users. Our experimental results on the image dataset from 100 users confirm the utility of hand geometry features with those from palmprints and achieve promising results with a simple image acquisition setup. © Springer-Verlag Berlin Heidelberg 2003.

关键词： image acquisition

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A general framework for machine vision: hierarchical token grouping

A general framework for machine vision: hierarchical token g...

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International Symposium on Speech, image processing and Neural Networks

作者： Qian Huang Pattern Recognition and Image Processing Laboratory Department of Computer Science Michigan State University East Lansing MI USA

ISBN: (纸本)078031865X

While the view of constructive and hierarchical vision prevails, the issues of cooperation and competition among individual modules become crucial. These issues are directly related to one of the most important aspects in computer vision research: integration. A major source of difficulty in developing a consistent and systematic integration formalism is the heterogeneity existing in modules, in information, and in knowledge. The author exploits, using the central theme of grouping, the homogeneous characteristics in vision problem solving and proposes a general framework, called hierarchical token grouping, that facilitates vision problem solving by providing a consistent and systematic environment for integrating modules, cues, and knowledge, all in a globally coherent mechanism.< >

关键词： Machine vision Problem-solving computer vision Organizing pattern recognition image processing Laboratories computer science Gratings Humans

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Theoretical Foundations of computer Vision 1

引用

丛书名： Computing Supplementa

1000年

作者： W. Kropatsch R. Klette F. Solina R. Albrecht

ISBN: (数字)9783709165867

ISBN: (纸本)9783211827307

computer Vision is a rapidly growing field of research investigating computational and algorithmic issues associated with image acquisition, processing, and understanding. It serves tasks like manipulation, recognition, mobility, and communication in diverse application areas such as manufacturing, robotics, medicine, security and virtual reality. This volume contains a selection of papers devoted to theoretical foundations of computer vision covering a broad range of fields, e.g. motion analysis, discrete geometry, computational aspects of vision processes, models, morphology, invariance, image compression, 3D reconstruction of shape. Several issues have been identified to be of essential interest to the community: non-linear operators; the transition between continuous to discrete representations; a new calculus of non-orthogonal partially dependent systems.

关键词： image processing and computer Vision pattern recognition Artificial Intelligence Combinatorics Differential Geometry Statistics, general

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Minimizing the topological structure of line images 7th

引用

7th Joint IAPR International Workshop on Structural and Syntactic pattern recognition, SSPR 1998 and 2nd International Workshop on Statistical Techniques in pattern recognition, SPR 1998

作者： Kropatsch, Walter G. Burge, Mark Vienna University of Technology Institute of Automation 183/2 Pattern Recognition and Image Processing Group Treitlstr.3 WienA-1040 Austria Johannes Kepler University Institute of Systems Science Computer Vision Laboratory LinzA-4040 Austria

ISBN: (纸本)3540648585

We present a new algorithm based on Dual Graph Contraction (DGC) to transform the Run Graph into its Minimum Line Property Preserving (MLPP) form which, when implemented in parallel, requires O(log(longestcurve)) steps. A MLPP graph of a line image compliments the structural information in geometric graph representations like the run graph. Using such a graph and its dual, line image analysis systems can efficiently detect topological features like loops and holes and make use of relations like containment. © Springer-Verlag Berlin Heidelberg 1998.

关键词： Topology

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