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SIGGRAPH Asia 2011 Courses, SA'11

作者： Filip, Jiří Haindl, Michal Pattern Recognition Department Institute of Information Theory and Automation of the AS CR Pod vodarenskou vezi 4 182 08 Praha 8 Czech Republic

ISBN: (纸本)9781450311359

Multidimensional visual texture is the appropriate paradigm for physically correct material visual properties representation. The course will present recent advances in texture modelling methodology as applied in computer vision, pattern recognition, computer graphics, and virtual/augmented reality applications. Contrary to previous courses on material appearance, we will focus on materials whose nature allows the exploitation of texture modeling approaches. This topic is introduced in the wider and complete context of pattern recognition and image processing. It comprehends modeling of multi-spectral images and videos which can be accomplished either with multi-dimensional mathematical models or sophisticated sampling methods from the original measurements. The key aspects of the topic, i.e., different multi-dimensional data models with their corresponding benefits and drawbacks, optimal model selection, parameter estimation and model synthesis techniques, are discussed. These methods produce compact parametric sets that not only faithfully reproduce material appearance, but are also vital for visual scene analysis, e.g. texture segmentation, classification, and retrieval. Special attention is devoted to recent advanced trends towards Bidirectional Texture Function (BTF) modeling, used for materials that do not obey Lambertian law, and whose reflectance has non-trivial illumination and viewing direction dependency. BTFs represent the best known effectively applicable textural representation of most real-world materials' visual properties. The techniques covered include efficient Markov random field-based algorithms, intelligent sampling algorithms, spatially-varying reflectance models and challenges with their possible implementation on GPU. The course also deals with proper data measurement, visualization of texture models in virtual scenes, visual quality evaluation feedback, as well as description of key industrial and research applications. We will discuss opti

关键词： Quality control

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16th Iberoamerican Congress on pattern recognition, CIARP 2011

作者： De Diego, Isaac Martín Siordia, Oscar S. Conde, Cristina Cabello, Enrique Face Recognition and Artificial Vision Group Universidad Rey Juan Carlos C. Tulipán S/N 28934 Móstoles Spain

ISBN: (纸本)9783642250842

The aim of this paper is to present a novelty methodology to develop similarity measures for classification of time series. First, a linear segmentation algorithm to obtain a section-wise representation of the series is presented. Then, two similarity measures are defined from the differences between the behavior of the series and the level of the series, respectively. The method is applied to subjective-data on time series generated through the evaluations of the driving risk from a group of traffic safety experts. These series are classified using the proposed similarities as kernels for the training of a Support Vector Machine. The results are compared with other classifiers using our similarities, their linear combination and the raw data. The proposed methodology has been successfully evaluated on several databases. © 2011 Springer-Verlag.

关键词： Time series

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Sparse acquisition and reconstruction for some computer vision problems

Sparse acquisition and reconstruction for some computer visi...

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作者： Reddy, Nagilla Dikpal University of Maryland College Park

学位级别：Ph.D.

Sparse representation, acquisition and reconstruction of signals guided by theory of Compressive Sensing (CS) has become an active research research topic over the last few years. Sparse representations effectively capture the idea of parsimony enabling novel acquisition schemes including sub-Nyquist sampling. Ideas from CS have had significant impact on well established fields such as signal acquisition, machine learning and statistics and have also inspired new areas of research such as low rank matrix completion. In this dissertation we apply CS ideas to low-level computer vision problems. The contribution of this dissertation is to show that CS theory is an important addition to the existing computational toolbox in computer vision and pattern recognition, particularly in data representation and processing. Additionally, in each of the problems we show how sparse representation helps in improved modeling of the underlying data leading to novel applications and better understanding of existing problems. In our work, the impact of CS is most felt in the acquisition of videos with novel camera designs. We build prototype cameras with slow sensors capable of capturing at an order of magnitude higher temporal resolution. First, we propose sub-Nyquist acquisition of periodic events and then generalize the idea to capturing regular events. Both the cameras operate by first acquiring the video at a slower rate and then computationally recovering the desired higher temporal resolution frames. In our camera, we sense the light with a slow sensor after modulating it with a fluttering shutter and then reconstruct the high speed video by enforcing its sparsity. Our cameras offer a significant advantage in light efficiency and cost by obviating the need to sense, transfer and store data at a higher frame rate. Next, we explore the applicability of compressive cameras for computer vision applications in bandwidth constrained scenarios. We design a compressive camera capable of

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Continuous emotion detection in response to music videos

Continuous emotion detection in response to music videos

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IEEE International Conference on Automatic Face and Gesture recognition

作者： Soleymani, Mohammad Koelstra, Sander Patras, Ioannis Pun, Thierry Computer Vision and Multimedia Laboratory University of Geneva Switzerland School of Computer Science and Electronic Engineering Queen Mary University of London United Kingdom

ISBN: (纸本)9781424491407

Viewers' preference for multimedia selection depends highly on their emotional experience. In this paper, we present an emotion detection method for music videos using central and peripheral nervous system physiological signals as well as multimedia content analysis. A set of 40 music clips eliciting a broad range of emotions were first selected. After extracting the one minute long emotional highlight of each video, they were shown to 32 participants while their physiological responses were recorded. Participants self-reported their felt emotions after watching each clip by means of arousal, valence, dominance, and liking ratings. The physiological signals included electroencephalogram, galvanic skin response, respiration pattern, skin temperature, electromyograms and blood volume pulse using plethysmograph. Emotional features were extracted from the signals and the multimedia content. The emotional features were used to train a linear ridge regressor to detect emotions for each participant using a leave-one-out cross-validation strategy. The performance of the personalized emotion detection is shown to be significantly superior to a random regressor. © 2011 IEEE.

关键词： Electrophysiology

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NonLinear refinement of structure from motion reconstruction by taking advantage of a partial knowledge of the environment

NonLinear refinement of structure from motion reconstruction...

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作者： Tamaazousti, Mohamed Gay-Bellile, Vincent Collette, Sylvie Naudet Bourgeois, Steve Dhome, Michel CEA LIST Vision and Content Engineering Lab Point Courrier 94 Gif-sur-Yvette F-91191 France LASMEA CNRS UBP 24 Avenue des Landais 63177 Aubière Cedex France

ISBN: (纸本)9781457703942

We address the challenging issue of camera localization in a partially known environment, i.e. for which a geometric 3D model that covers only a part of the observed scene is available. When this scene is static, both known and unknown parts of the environment provide constraints on the camera motion. This paper proposes a nonlinear refinement process of an initial SfM reconstruction that takes advantage of these two types of constraints. Compare to those that exploit only the model constraints i.e. the known part of the scene, including the unknown part of the environment in the optimization process yields a faster, more accurate and robust refinement. It also presents a much larger convergence basin. This paper will demonstrate these statements on varied synthetic and real sequences for both 3D object tracking and outdoor localization applications. © 2011 IEEE.

关键词： Cameras

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Proceedings of the 2011 International Conference on pattern Analysis and Intelligent Robotics, ICPAIR 2011

Proceedings of the 2011 International Conference on Pattern ...

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2011 International Conference on pattern Analysis and Intelligent Robotics, ICPAIR 2011

ISBN: (纸本)9781612844046

The proceedings contain 43 papers. The topics discussed include: intelligence technology for cyber-physical robot system;vision-based automatic incident detection system using image sequences for intersections;new image compression algorithm using proposed quantization approach;neighborhood discriminative manifold projection for face recognition in video;shock coupled coherence enhancing diffusion for robust core-point detection in fingerprints;a modified three level block truncation coding for image compression;mobile learning course content application as a revision tool: the effectiveness and usability;accessible targets for motion impaired users with hidden click zone technique;remedial software for negative numbers subtraction operation: meta-cognitive/constructivism approach;factoring culture as the main role to design game interface model;and self efficiency and social influence of computer support collaborative learning teaching and learning blog.

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Shape Analysis of Agricultural Products: A Review of Recent Research Advances and Potential Application to computer vision

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FOOD AND BIOPROCESS TECHNOLOGY 2011年第5期4卷 673-692页

作者： Costa, Corrado Antonucci, Francesca Pallottino, Federico Aguzzi, Jacopo Sun, Da-Wen Menesatti, Paolo CRA ING Agr Engn Res Unit Agr Res Council I-00015 Rome Italy Inst Ciencias Mar ICM CSIC Barcelona 08003 Spain Univ Coll Dublin Agr & Food Sci Ctr Dublin 4 Ireland

The appearance of agricultural products deeply conditions their marketing. Appearance is normally evaluated by considering size, shape, form, colour, freshness condition and finally the absence of visual defects. Among these features, the shape plays a crucial role. Description of agricultural product shape is often necessary in research fields for a range of different purposes, including the investigation of shape traits heritability for cultivar descriptions, plant variety or cultivar patents and evaluation of consumer decision performance. This review reports the main applications of shape analysis on agricultural products such as relationships between shape and: (1) genetic;(2) conformity and condition ratios;(3) products characterization;(4) product sorting and finally, (5) clone selection. Shape can be a protagonist of evaluation criteria only if an appreciable level of image shape processing and automation and data are treated with solid multivariate statistic. In this context, image-processing algorithms have been increasingly developed in the last decade in order to objectively measure the external features of agricultural products. Grading and sorting of agricultural products using machine vision in conjunction with pattern recognition techniques offers many advantages over the conventional optical or mechanical sorting devices. With this aims, we propose a new automated shape processing system which could be useful for both scientific and industrial purposes, forming the bases of a common language for the scientific community. We applied such a processing scheme to morphologically discriminate nuts fruit of different species. Operative Matlab codes for shape analysis are reported.

关键词： Image analysis Shape analysis Agricultural products Multivariate statistics

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Feature extraction technique to reduce dimensionality of the acquired THz spectra response

Feature extraction technique to reduce dimensionality of the...

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Conference on Millimetre Wave and Terahertz Sensors and Technology IV

作者： Ryniec, Radoslaw Szustakowski, Mieczyslaw Zagrajek, Przemyslaw Piszczek, Marek Mil Univ Technol PL-00908 Warsaw Poland

ISBN: (纸本)9780819488169

Recently, there has been a significant interest in employing Terahertz (THz) technology, spectroscopy and imaging for standoff detection. The main advantage of terahertz systems is the possibility for remote detect and identification of chemical compounds. Practical security system in reflection mode is desired. Unfortunately, reflection spectra for many compounds are very similar. Therefore, the simple correlation method is not sufficient to distinguish substances. In this paper we present the concept of using combined techniques of Short Time Fourier Transform (SFFT) and image processing with pattern recognition application in the area of automatic identification of explosives in THz range.

关键词： identification explosives THz computer vision

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Evaluation of RSL History as a Tool for Assistance in the Development and Evaluation of computer vision Algorithms

Evaluation of RSL History as a Tool for Assistance in the De...

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作者： Holm, Ben Rochester Institute of Technology

学位级别：M.S.

A revision of recognition Strategy Language (RSL), a domain-specific language for pattern recognition algorithm development, is in development. This language provides several tools for pattern recognition algorithm implementation and analysis, including composition of operations and a detailed history of those operations and their results. This research focuses on that history and shows that for some problems it provides an improvement over traditional methods of gathering information. When designing a pattern recognition algorithm, bookkeeping code in the form of copious logging and tracing code must be written and analyzed in order to test the effectiveness of procedures and parameters. The amount of data grows when dealing with video streams; new organization and searching tools need to be designed in order to manage the large volume of data. General purpose languages have techniques like Aspect Oriented Programming intended to address this problem, but a general approach is limited because it does not provide tools that are useful to only one problem domain. By incorporating support for this bookkeeping work directly into the language, RSL provides an improvement over the general approach in both development time and ability to evaluate the algorithm being designed for some problems. The utility of RSL is tested by evaluating the implementation process of a computer vision algorithm for recognizing American Sign Language (ASL). RSL history is examined in terms of its use in the development and evaluation stages of the algorithm, and the usefulness of the history is stated based on the benefit seen at each stage. RSL is found to be valuable for a portion of the algorithm involving distinct steps that provide opportunity for comparison. RSL was less beneficial for the dynamic programming portion of the algorithm. Compromises were made for performance reasons while implementing the dynamic programming solution and the inspection at every step of what amounts to a b

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Identifying potentially cancerous tissues in chromoendoscopy images

Identifying potentially cancerous tissues in chromoendoscopy...

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5th Iberian Conference on pattern recognition and Image Analysis, IbPRIA 2011

作者： Riaz, Farhan Vilarino, Fernando Ribeiro, Mario Dinis Coimbra, Miguel Instituto de Telecomunicacoes Universidade do Porto Portugal Computer Vision Center Universitate Autónoma de Barcelona Spain Instituto Portugues Oncologia Porto Portugal

ISBN: (纸本)9783642212567

The dynamics of image acquisition conditions for gastroenterology imaging scenarios pose novel challenges for automatic computer assisted decision systems. Such systems should have the ability to mimic the tissue characterization of the physicians. In this paper, our objective is to compare some feature extraction methods to classify a Chromoendoscopy image into two different classes: Normal and Potentially cancerous. Results show that LoG filters generally give best classification accuracy among the other feature extraction methods considered. © Springer-Verlag Berlin Heidelberg 2011.

关键词： Tissue

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