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"De-Ghosting" Artifact in Scene-Based Nonuniformity Correction of Infrared Image Sequences

16th Iberoamerican Congress on pattern recognition

作者： Jara, Anselmo Torres, Flavio Univ La Frontera Dept Elect Engn Temuco Chile

ISBN: (纸本)9783642250842

In this paper we present a new technique to improve the convergence and to reduce the ghosting artifacts based on constant statistics (CS) method. We propose to reduce ghosting artifacts and to speed up the convergence by using enhanced constant statistics method with the motion threshold. The key advantage of the method is based in its capacity for estimate detectors parameters, and then compensate for fixed-pattern noise in a frame by frame basics. The ability of the method to compensate for nonuniformity and reducing ghosting artifacts is demonstrated by employing video sequences of simulated and several infrared video sequences obtained using two infrared cameras.

关键词： Infrared detectors focal-plane array non-uniformity correction fixed-pattern noise ghosting artifact

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Obliterable of Graphics and Correction of Skew using Hough Transform for Mobile captured Documents

Obliterable of Graphics and Correction of Skew using Hough T...

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International Conference on Graphic and Image Processing (ICGIP)

作者： Chethan, H. K. Kumar, G. Hemantha Univ Mysore Dept Studies Comp Sci Mysore 570005 Karnataka India

ISBN: (纸本)9780819489326

CBDA is an emerging field in computer vision and pattern recognition. In recent technology camera are incorporated to several electronic equipments and are very interesting and thus playing a vital role by replacing scanner with hand held imaging devices like Digital Cameras, Mobile phones and gaming devices attached with these camera. The goal of the work is to remove graphics from the document which plays a vital role in recognition of characters from the mobile captured documents. In this paper we have proposed a novel method for separating or removal of graphics like logos, animations other than the text from the document and method to reduce noise and finally textual content skew is estimated and corrected using Hough Transform. The experimental results show the efficacy compared to the result of well known existing methods.

关键词： CBDA computer vision Skew graphics pattern recognition HIDs Hough Transform

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pattern recognition 2011年第9期44卷 2063-2075页

作者： Chambon, Sylvie Crouzil, Alain Ctr Nantes Route Bouaye MACS IFSTTAR AI F-44341 Bouguenais France TCI IRIT UPS F-31062 Toulouse 9 France

In the context of computer vision, matching can be done with similarity measures. This paper presents the classification of these measures into five families. In addition, 18 measures based on robust statistics, previously proposed in order to deal with the problem of occlusions, are studied and compared to the state of the art. A new evaluation protocol and new analyses are proposed and the results highlight the most efficient measures, first, near occlusions, the smooth median powered deviation, and second, near discontinuities, a non-parametric transform-based measure, CENSUS. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Stereo vision Image matching Similarity Correlation Occlusions

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vision processing for position based visual servo control of spherical objects

Vision processing for position based visual servo control of...

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2011 International Conference on Image Processing, computer vision, and pattern recognition, IPCV 2011

作者： Edmondson, M.C. Tang, L. School of Engineering and Advanced Technology Massey University New Zealand

ISBN: (纸本)9781601321916

There is an need for an autonomous system that can organise spherical objects and reposition these objects with six degrees of control. A mechatronic system is intended to partially fulfil the needs of this system by providing the means to position an object's three degrees of rotational freedom. In this paper we present the development of a vision motion tracking algorithm. This algorithm is then to be used for creation of motion models and a visual servo system. The vision algorithm is based around intra-frame blob tracking to determine the motion of a manipulated object. The common axis and magnitude of the motion is determined by tracking randomly placed dots on the object's surface. An intersection of planes approach is utilised to generate a best fit axis of rotation. The performance of the dot tracking and axis rotation algorithms are investigated with simulations by varying variables test against other methodologies.

关键词： Visual servoing

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Action recognition with multiscale spatio-temporal contexts

Action recognition with multiscale spatio-temporal contexts

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作者： Wang, Jiang Chen, Zhuoyuan Wu, Ying EECS Department Northwestern University 2145 Sheridan Road Evanston IL 60208 United States

ISBN: (纸本)9781457703942

The popular bag of words approach for action recognition is based on the classifying quantized local features density. This approach focuses excessively on the local features but discards all information about the interactions among them. Local features themselves may not be discriminative enough, but combined with their contexts, they can be very useful for the recognition of some actions. In this paper, we present a novel representation that captures contextual interactions between interest points, based on the density of all features observed in each interest point's mutliscale spatio-temporal contextual domain. We demonstrate that augmenting local features with our contextual feature significantly improves the recognition performance. © 2011 IEEE.

关键词： pattern recognition

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Spatio-Temporal Context Kernel for Activity recognition

Spatio-Temporal Context Kernel for Activity Recognition

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1st Asian Conference on pattern recognition (ACPR)

作者： Yuan, Fei Sahbi, Hichem Prinet, Veronique Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Beijing Peoples R China TELECOM ParisTech CNRS LTCI Paris France

ISBN: (纸本)9781457701214;9781457701221

Local space-time features and bag-of-feature (BOF) representation are often used for action recognition in previous approaches. For complicated human activities, however, the limitation of these approaches blows up because of the local properties of features and the lack of context. This paper addresses the problem by exploiting the spatio-temporal context information between features. We first define a spatio-temporal context, which combines the scale invariant spatio-temporal neighberhood of local features with the spatio-temporal relationships between them. Then, we introduce a spatio-temporal context kernel (STCK), which not only takes into account the local properties of features but also considers their spatial and temporal context information. STCK has a promising generalization property and can be plugged into SVMs for activities recognition. The experimental results on challenging activity datasets show that, compared to context-free model, the spatio-temporal context kernel improves the recognition performance.

关键词： computer vision Context Humans Kernel pattern recognition Support vector machines Videos

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Extracting local texture features for image-based coin recognition

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IET IMAGE PROCESSING 2011年第5期5卷 394-401页

作者： Shen, L. Jia, S. Ji, Z. Chen, W. -S. ShenZhen Univ Sch Comp Sci & Software Engn Shenzhen Guangdong Peoples R China Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100088 Peoples R China ShenZhen Univ Sch Math Shenzhen Peoples R China

The authors propose to extract local texture features for image-based coin recognition in this study. A set of Gabor wavelets and local binary pattern (LBP) operator are employed to represent texture information. Concentric ring structure is used to divide the coin image into a number of small sections. Statistics of Gabor coefficients or LBP values within each section is then concatenated into a feature vector to represent the image. A circular shift operator is proposed to make Gabor features robust against rotation variance. Matching between two coin images is done via distance measurement. The nearest-neighbour classifier is used to classify a given test coin. The public MUSCLE database consisting of over 10 000 images is used to test our algorithms;results show that significant improvements over edge distance-based methods have been achieved. The authors have also analysed the performance of the system on recognising unregistered coins and the analysis suggests further improvement could be achieved if physical properties like diameter and thickness are included for feature representation.

关键词： Image recognition feature representation computer vision and image processing techniques local binary pattern operator Gabor filters MUSCLE database image based coin recognition feature extraction Gabor wavelets image texture local texture feature extraction circular shift operator

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DTW for Matching Radon Features: A pattern recognition and Retrieval Method

DTW for Matching Radon Features: A Pattern Recognition and R...

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13th International Conference on Advanced Concepts for Intelligent vision Systems (ACIVS) / 5th ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC)

作者： Santosh, K. C. Lamiroy, Bart Wendling, Laurent INRIA Nancy Grand Est Res Ctr LORIA Campus SciBP 239 F-54506 Vandoeuvre Les Nancy France Nancy Univ INPL LORIA F-54506 Nancy France Univ Paris 05 LIPADE F-75270 Nancy France

ISBN: (纸本)9783642236877

In this paper, we present a method for pattern such as graphical symbol and shape recognition and retrieval. It is basically based on dynamic programming for matching the Radon features. The key characteristic of the method is to use DTW algorithm to match corresponding pairs of histograms at every projecting angle. This allows to exploit the Radon property to include both boundary as internal structure of shapes, while avoiding compressing pattern representation into a single vector and thus miss information, thanks to the DTW. Experimental results show that the method is robust to distortion and degradation including affine transformations.

关键词： Radon Transform DTW pattern recognition and Retrieval

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Circle Detection Based on Multiscale Edge Curvature Estimation

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pattern recognition and Image Analysis 2011年第2期21卷 318-320页

作者： Semeikina, E.V. Yurin, D.V. Faculty of Computational Mathematics and Cybernetics Laboratory of Mathematical Methods of Image Processing Moscow State University Leninskie gory Moscow 119992 Russia

A procedure for adapting the isoline curvature formula to estimate an edge curvature in the images is presented. The curvature estimation is used in the framework of the scale-space algorithm, which makes it possible to choose the required scale adaptively at each point of interest. The procedure for edge points clustering to the subsets, each of which contains the points of one circumference, has been developed to detect the circumferences. © 2011 Pleiades Publishing, Ltd.

关键词： computer vision

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Mining Layered Grammar Rules for Action recognition

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INTERNATIONAL JOURNAL OF computer vision 2011年第2期93卷 162-182页

作者： Wang, Liang Wang, Yizhou Gao, Wen Peking Univ Natl Engn Lab Video Technol Beijing 100871 Peoples R China Peking Univ Key Lab Machine Percept MoE Sch Elect Engn & Comp Sci Beijing 100871 Peoples R China Harbin Inst Technol Sch Comp Sci & Technol Harbin 150006 Heilongjiang Peoples R China

We propose a layered-grammar model to represent actions. Using this model, an action is represented by a set of grammar rules. The bottom layer of an action instance's parse tree contains action primitives such as spatiotemporal (ST) interest points. At each layer above, we iteratively mine grammar rules and "super rules" that account for the high-order compositional feature structures. The grammar rules are categorized into three classes according to three different ST-relations of their action components, namely the strong relation, weak relation and stochastic relation. These ST-relations characterize different action styles (degree of stiffness), and they are pursued in terms of grammar rules for the purpose of action recognition. By adopting the Emerging pattern (EP) mining algorithm for relation pursuit, the learned production rules are statistically significant and discriminative. Using the learned rules, the parse tree of an action video is constructed by combining a bottom-up rule detection step and a top-down ambiguous rule pruning step. An action instance is recognized based on the discriminative configurations generated by the production rules of its parse tree. Experiments confirm that by incorporating the high-order feature statistics, the proposed method largely improves the recognition performance over the bag-of-words models.

关键词： Action recognition Layered-grammar model Action parse tree Emerging pattern mining

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