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Adaptive and Natural Computing Algorithms - 10th International Conference, ICANNGA 2011, Proceedings

Adaptive and Natural Computing Algorithms - 10th Internation...

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10th International Conference on Adaptive and Natural Computing Algorithms, ICANNGA 2011

ISBN: (纸本)9783642202667

The proceedings contain 84 papers. The topics discussed include: new measure of boolean factor analysis quality;mechanisms of adaptive spatial integration in a neural model of cortical motion processing;self-organized short-term memory mechanism in spiking neural network;approximation of functions by multivariable hermite basis: a hybrid method;using pattern recognition to predict driver intent;neural networks committee for improvement of metal's mechanical properties estimates;logarithmic multiplier in hardware implementation of neural networks;a robust learning model for dealing with missing values in many-core architectures;a model of saliency-based selective attention for machine vision inspection application;grapheme-phoneme translator for Brazilian Portuguese;and improvement of inventory control under parametric uncertainty and constraints.

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On the matching of images containing repetitive patterns by pairs of interest points

On the matching of images containing repetitive patterns by ...

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2011 International Conference on Information Science and Technology, ICIST 2011

作者： Fan, Bin Wu, Fuchao Hu, Zhanyi National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781424494408

Image matching is a fundamental task for computer vision. However, due to the local ambiguities induced by repetitive patterns in most of man-made objects or scenes, matching images of repetitive patterns is still a challenging problem even the viewpoint changes of them are not very large. This paper is primarily focused on the problem of matching images containing repetitive patterns and proposes a novel method based on pairs of interest points to solve the problem. It starts from matching pairs of interest points and then obtaining point correspondences from the matched point-pairs based on the low distortion constraint, which is meant that the distortions of point groups should be small across images. By combing pairs of interest points, local ambiguities induced by repetitive patterns can be reduced to some extent since information in a much larger region is used. Moreover, owing to our newly defined compatibility measure between one correspondence and a set of point correspondences, the obtained point correspondences are very reliable. Experimental results have demonstrated the effectiveness of the proposed method as well as its superiority to the existing methods. © 2011 IEEE.

关键词： Problem solving

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Non-english and non-latin signature verification systems: A survey

Non-english and non-latin signature verification systems: A ...

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1st International Workshop on Automated Forensic Handwriting Analysis, AFHA 2011 - A Satellite Workshop of ICDAR 2011

作者： Pal, Srikanta Blumenstein, Michael Pal, Umapada School of Information and Communication Technology Griffith University QLD Australia Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata-700108 India

Signatures continue to be an important biometric because they remain widely used as a means of personal verification and therefore an automatic verification system is needed. Manual signature-based authentication of a large number of documents is a difficult and time consuming task. Consequently for many years, in the field of protected communication and financial applications, we have observed an explosive growth in biometric personal authentication systems that are closely connected with measurable unique physical characteristics (e.g. hand geometry, iris scan, finger prints or DNA) or behavioural features. Substantial research has been undertaken in the field of signature verification involving English signatures, but to the best of our knowledge, very few works have considered non-English signatures such as Chinese, Japanese, Arabic etc. In order to convey the state-of-the-art in the field to researchers, in this paper we present a survey of non-English and non-Latin signature verification systems.

关键词： Biometrics

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A Fast Interactive Image Segmentation to Locate Multiple Similar-colored Objects

A Fast Interactive Image Segmentation to Locate Multiple Sim...

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National Conference on computer vision, pattern recognition, Image Processing and Graphics (NCVPRIPG)

作者： Bibhas Chandra Dhara Bhabatosh Chanda Department of Information Technology Jadavpur University Kolkata India Electronics and Communication Sciences Unit Indian Statistical Institute Kolkata India

A fundamental problem in image processing is image segmentation. The conventional image segmentation methods, to some extent, all suffe from the problem of inaccurate segmentation. A slightly easier and more approachable problem - interactive segmentation - has also received a lot of attentions over the years. In this paper, we propose a fast and simple interactive image segmentation technique. This segmentation process is conducted in two modules. First, the original image is pre-segmented by a low level segmentation method. Second, some portion of the object-of-interest is marked. The proposed method identifies all the similar-colored objects present in the image. In this work, color feature is used to measure the closeness between two regions and accordingly the label of the unmarked region is decided.

关键词： Image segmentation Merging computer vision Image color analysis Histograms Object recognition

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Functional Categorization of Objects using Real-time Markerless Motion Capture

Functional Categorization of Objects using Real-time Markerl...

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IEEE Conference on computer vision and pattern recognition

作者： Juergen Gall Andrea Fossati Luc van Gool BIWI ETH Zurich ESAT-PSI/IBBT KU Leuven

ISBN: (纸本)9781457703942

Unsupervised categorization of objects is a fundamental problem in computer vision. While appearance-based methods have become popular recently, other important cues like functionality are largely neglected. Motivated by psychological studies giving evidence that human demonstration has a facilitative effect on categorization in infancy, we propose an approach for object categorization from depth video streams. To this end, we have developed a method for capturing human motion in real-time. The captured data is then used to temporally segment the depth streams into actions. The set of segmented actions are then categorized in an unsupervised manner, through a novel descriptor for motion capture data that is robust to subject variations. Furthermore, we automatically localize the object that is manipulated within a video segment, and categorize it using the corresponding action. For evaluation, we have recorded a dataset that comprises depth data with registered video sequences for 6 subjects, 13 action classes, and 174 object manipulations.

关键词： images computer vision motion capture Psychological Studies Taxonomy infancy

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Exhaustive Family of Energies Minimizable Exactly by a Graph Cut

Exhaustive Family of Energies Minimizable Exactly by a Graph...

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IEEE Conference on computer vision and pattern recognition

作者： Guillaume Charpiat Pulsar team INRIA

ISBN: (纸本)9781457703942

Graph cuts are widely used in many fields of computer vision in order to minimize in small polynomial time complexity certain classes of energies. These specific classes depend on the way chosen to build the graphs representing the problems to solve. We study here all possible ways of building graphs and the associated energies minimized, leading to the exhaustive family of energies minimizable exactly by a graph cut. To do this, we consider the issue of coding pixel labels as states of the graph, i.e. the choice of state interpretations. The family obtained comprises many new classes, in particular energies that do not satisfy the submodularity condition, including energies that are even not permuted-submodular. A generating subfamily is studied in details, in particular we propose a canonical form to represent Markov random fields, which proves useful to recognize energies in this subfamily in linear complexity almost surely, and then to build the associated graph in quasilinear time. A few experiments are performed, to illustrate the new possibilities offered.

关键词： Line graph images computer vision Energy sources subfamily Markov random fields linear complexity Canonical form family Cutting

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Symmetric Piecewise Planar Object Reconstruction from a Single Image

Symmetric Piecewise Planar Object Reconstruction from a Sing...

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IEEE Conference on computer vision and pattern recognition

作者： Tianfan Xue Jianzhuang Liu Xiaoou Tang Department of Information Engineering The Chinese University of Hong Kong

ISBN: (纸本)9781457703942

Recovering 3D geometry from a single view of an object is an important and challenging problem in computer vision. Previous methods mainly focus on one specific class of objects without large topological changes, such as cars, faces, or human bodies. In this paper, we propose a novel single view reconstruction algorithm for symmetric piecewise planar objects that are not restricted to some object classes. Symmetry is ubiquitous in manmade and natural objects and provides rich information for 3D reconstruction. Given a single view of a symmetric piecewise planar object, we first find out all the symmetric line pairs. The geometric properties of symmetric objects are used to narrow down the searching space. Then, based on the symmetric lines, a depth map is recovered through a Markov random field. Experimental results show that our algorithm can efficiently recover the 3D shapes of different objects with significant topological variations.

关键词： images three-dimensional displays CENTROSYMMETRIC computer vision Piecewise Human Body Planar

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Global temporal registration of multiple non-rigid surface sequences

Global temporal registration of multiple non-rigid surface s...

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IEEE Conference on computer vision and pattern recognition

作者： Peng Huang Chris Budd Adrian Hilton Centre for Vision Speech Signal Processing University of Surrey

ISBN: (纸本)9781457703942

In this paper we consider the problem of aligning multiple non-rigid surface mesh sequences into a single temporally consistent representation of the shape and motion. A global alignment graph structure is introduced which uses shape similarity to identify frames for inter-sequence registration. Graph optimisation is performed to minimise the total non-rigid deformation required to register the input sequences into a common structure. The resulting global alignment ensures that all input sequences are resampled with a common mesh structure which preserves the shape and temporal correspondence. Results demonstrate temporally consistent representation of several public databases of mesh sequences for multiple people performing a variety of motions with loose clothing and hair.

关键词： Shape Surface reconstruction Three dimensional displays Databases Silicon Tracking Registers

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Fast and High-Performance Template Matching Method

Fast and High-Performance Template Matching Method

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IEEE Conference on computer vision and pattern recognition

作者： Alexander Sibiryakov ASL Vision

ISBN: (纸本)9781457703942

This paper proposes a new template matching method that is robust to outliers and fast enough for real-time operation. The template and image are densely transformed in binary code form by projecting and quantizing histograms of oriented gradients. The binary codes are matched by a generic method of robust similarity applicable to additive match measures, such as L_p- and Hamming distances. The robust similarity map is computed efficiently via a proposed Inverted Location Index structure that stores pixel locations indexed by their values. The method is experimentally justified in large image patch datasets. Challenging applications, such as intra-category object detection, object tracking, and multimodal image matching are demonstrated.

关键词： Fasting TEMPLATE MATCHING image matching binary code outliers Ham Imagery (Psychotherapy) images image patch REAL TIME OPERATION Hamming distance Robustness

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Exploring Relations of Visual Codes for Image Classification

Exploring Relations of Visual Codes for Image Classification

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IEEE Conference on computer vision and pattern recognition

作者： Yongzhen Huang Kaiqi Huang Chong Wang Tieniu Tan National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781457703942

The classic Bag-of-Features (BOF) model and its extensional work use a single value to represent a visual code. This strategy ignores the relation of visual codes. In this paper, we explore this relation and propose a new algorithm for image classification. It consists of two main parts: 1) construct the codebook graph wherein a visual code is linked with other codes;2) describe each local feature using a pair of related codes, corresponding to an edge of the graph. Our approach contains richer information than previous BOF models. Moreover, we demonstrate that these models are special cases of ours. Various coding and pooling algorithms can be embedded into our framework to obtain better performance. Experiments on different kinds of image classification databases demonstrate that our approach can stably achieve excellent performance compared with various BOF models.

关键词： Image classification Basic oxygen converters Codes Visualization local image feature monodromy

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