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Unsupervised Effectiveness Estimation for image Retrieval using Reciprocal Rank Information 28

Unsupervised Effectiveness Estimation for Image Retrieval us...

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28th SIBGRAPI Conference on graphics, Patterns and images SIBGRAPI

作者： Guimaraes Pedronette, Daniel Carlos Torres, Ricardo da S. State Univ Sao Paulo UNESP Dept Stat Appl Math & Comp Rio Claro Brazil Univ Campinas UNICAMP Inst Comp Recod Lab Campinas SP Brazil

ISBN: (纸本)9781467379625

In this paper, we present an unsupervised approach for estimating the effectiveness of image retrieval results obtained for a given query. The proposed approach does not require any training procedure and the computational efforts needed are very low, since only the top-k results are analyzed. In addition, we also discuss the use of the unsupervised measures in two novel rank aggregation methods, which assign weights to ranked lists according to their effectiveness estimation. An experimental evaluation was conducted considering different datasets and various image descriptors. Experimental results demonstrate the capacity of the proposed measures in correctly estimating the effectiveness of different queries in an unsupervised manner. The linear correlation between the proposed and widely used effectiveness evaluation measures achieves scores up to 0.86 for some descriptors.

关键词： content-based image retrieval unsupervised effectiveness estimation query difficult prediction

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Assessing Facial image Accordance to ISO/ICAO Requirements

Assessing Facial Image Accordance to ISO/ICAO Requirements

引用

brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： R. L. Parente Leonardo V. Batista Igor L. P. Andrezza Erick V. C. L. Borges Rajiv A. T. Mota Informatics Center-CI Federal University of Paraíba-UFPB João Pessoa Brazil VSoft Tecnologia João Pessoa PB Brasil

ISBN: (纸本)9781509035694;9781509035687

Face has been adopted as default biometric validation method and the International Standard Organization (ISO) proposed a standard which states constraints for facial image. This paper presents methods for evaluating face image conformance to the following ISO/ICAO requirements: pixelation, hair across eyes, veil over face and mouth opened. Each requirement is individually evaluated. The algorithm for analyzing pixelation achieved an equal error rate (EER) equals to 1.7%, result very close to state-of-the-art (0.0% EER). The "Hair Across Eyes" analysis method achieved an EER equals to 11.9% which surpass the best state-of-art result (12.4%). The algorithm for evaluating "Veil Over Face" requirement achieved EER equals to 1.2% which also surpass the best state-of-art result (2.5%). The "Mouth Opened" requirement achieved an EER equals to 4.20%, a result compatible with state-of-art rates for this requirement (3.3%).

关键词： image color analysis Face Mouth Hair image quality Databases Skin

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Enhancement of Underwater images in Low-to-High Turbidity Rivers

Enhancement of Underwater Images in Low-to-High Turbidity Ri...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Daily Daleno de O. Rodrigues Wagner F. de Barros José P. de Queiroz-Neto Anderson G. Fontoura José Reginaldo H. Carvalho Instituto Federal do Amazonas (IFAM) Manaus Brazil Instituto Federal de Educacao Ciencia e Tecnologia do Norte de Minas Gerais Montes Claros MG BR Instituto Federal de Educacao Ciencia e Tecnologia do Amazonas Manaus AM BR Instituto de Computação (IComp) Universidade Federal do Amazonas (UFAM) Manaus Brazil

ISBN: (纸本)9781509035694;9781509035687

The demand for efficient enhancement methods of underwater images of the rivers in the Amazon region is increasing. However, most of those in the region present moderate turbidity and low luminosity. This work aims to improve these images by non-linear filtering techniques, which promote the minimization of light interaction characteristics with the environment, loss of the contrast and colors. The proposed method is compared with two others techniques that requires a unique image as input. The results of the proposed method is promising, with better visual quality considering a wide range of experiments with simulation data and real outdoor scenes.

关键词： image color analysis Lighting Cameras Mathematical model Rivers Histograms Frequency-domain analysis

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Complexity-Aware Assignment of Latent Values in Discriminative Models for Accurate Gesture Recognition

Complexity-Aware Assignment of Latent Values in Discriminati...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Manoel Horta Ribeiro Bruno Teixeira Antônio Otávio Fernandes Wagner Meira Erickson R. Nascimento Computer Science Department Universidade Federal de Minas Gerais (UFMG) Brazil

Many of the state-of-the-art algorithms for gesture recognition are based on Conditional Random Fields (CRFs). Successful approaches, such as the Latent-Dynamic CRFs, extend the CRF by incorporating latent variables, whose values are mapped to the values of the labels. In this paper we propose a novel methodology to set the latent values according to the gesture complexity. We use an heuristic that iterates through the samples associated with each label value, estimating their complexity. We then use it to assign the latent values to the label values. We evaluate our method on the task of recognizing human gestures from video streams. The experiments were performed in binary datasets, generated by grouping different labels. Our results demonstrate that our approach outperforms the arbitrary one in many cases, increasing the accuracy by up to 10%.

关键词： Hidden Markov models Complexity theory Graphical models Gesture recognition Activity recognition Computational modeling Random variables

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Decreasing the Number of Features for Improving Human Action Classification

Decreasing the Number of Features for Improving Human Action...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Kleber Jacques De Souza Arnaldo de Albuquerque Araújo Zenilton Kleber G. do Patrocínio Jean Cousty Laurent Najman Yukiko Kenmochi Silvio Jamil F. Guimarães Universidade Federal de Minas Gerais Belo Horizonte MG BR Comput. Sci. Dept. Fed. Univ. of Minas Gerais Belo Horizonte Brazil Audio-Visual Information Proc. Lab. (VIPLAB)Computer Science Department – ICEI – PUC Minas Université Paris-Est Laboratoire d'Informatique Gaspard-Monge UMR 8049 Noisy-le-Grand France Computer Science Department Audio-Visual Information Proc. Lab. (VIPLAB)

Action classification in videos has been a very active field of research over the past years. Human action classification is a research field with application to various areas such as video indexing, surveillance, human-computer interfaces, among others. In this paper, we propose a strategy based on decreasing the number of features in order to improve accuracy in the human action classification task. Thus, to classify human action, we firstly compute a video segmentation for simplifying the visual information, in the following, we use a mid-level representation for representing the feature vectors which are finally classified. Experimental results demonstrate that our approach has improved the quality of human action classification in comparison to the baseline while using 60% less features.

关键词： Videos Feature extraction Motion segmentation Trajectory YouTube Visualization image segmentation

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A Genetically Programmable Hybrid Virtual Reconfigurable Architecture for image Filtering Applications

A Genetically Programmable Hybrid Virtual Reconfigurable Arc...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： M. A. Almeida Emerson Carlos Pedrino M. C. Nicoletti Computer Science Dept. UFSCar S. Carlos SP Brazil Computer Science Dept. UFSCar & FACCAMP SP Brazil

ISBN: (纸本)9781509035694;9781509035687

A new and efficient automatic hybrid method, called Hy-EH, based on Virtual Reconfigurable Architectures (VRAs) and implemented in Field Programmable Gate Arrays (FPGAs) is proposed, for a hardware-embedded construction of image filters. The method also encompass an evolutionary software system, which represents the chromosome as a bi-dimensional grid of function elements (FEs), entirely parameterized using the Verilog-HDL (Verilog Hardware Description Language), which is reconfigured using the MATLAB toolbox GPLAB, before its download into the FPGA. In the so-called intrinsic proposals, evolutionary processes take place internally to the hardware, in a pre-defined fixed way, in extrinsic proposals evolutionary processes happen externally to the hardware. The hybrid Hy-EH method, described in this paper allows for the intrinsic creation of a flexible-sized hardware, in an extrinsic way i.e., by means of an evolutionary process that happens externally to the hardware. Hy-EH is also a convenient choice as far as extrinsic methods are considered, since it does not depend on a proprietary solution for its implementation. A comparative analysis of using the Hy-EH versus an existing intrinsic proposal, in two well-known problems, has been conducted. Results show that by using Hy-EH there was little hardware complexity due to the optimized and more flexible use of shorter chromosomes.

关键词： Biological cells Hardware Iron Field programmable gate arrays Hardware design languages computer architecture Noise measurement

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A High Density Colored 2D-Barcode: CQR Code-9

A High Density Colored 2D-Barcode: CQR Code-9

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Max E. Vizcarra Melgar Mylène C. Q. Farias Flávio de Barros Vidal Alexandre Zaghetto Universidade de Brasilia Brasilia DF BR University of Brasilia Brasilia DF Brazil

ISBN: (纸本)9781509035694;9781509035687

This paper presents an implementation of a colored 2D-barcode which is based on the structure of the CQR Code (Colored Quick Response Code). While the first version of the CQR Code (CQR Code-5) is a 2-D barcode of 5 colors, this new version (CQR Code-9) has 9 colors. In this paper we describe the implementation details of this new CQR Code. This new version of the CQR Code can store up to 2,048 information bits, requiring 4,576 redundancy bits. The Reed-Solomon error correction algorithm provides an error correction rate of 34.54%. Experimental tests were performed by printing CQR Codes in a 1.3 cm × 1.3 cm area. Results show that the CQR Code-9 is suitable for cryptographic applications that require that a high number of bits be stored in a small printed area.

关键词： image color analysis Decoding Encoding Redundancy Reed-Solomon codes Error correction image segmentation

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Partial Least Squares image Clustering 28

Partial Least Squares Image Clustering

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28th SIBGRAPI Conference on graphics, Patterns and images SIBGRAPI

作者： Kloss, Ricardo Barbosa Cirne, Marcos Vinicius Mussel Silva, Samira Pedrini, Helio Schwartz, William Robson Univ Fed Minas Gerais Dept Comp Sci Belo Horizonte MG Brazil Univ Estadual Campinas Inst Comp Campinas SP Brazil

ISBN: (纸本)9781467379625

Clustering techniques have been widely used in areas that handle massive amounts of data, such as statistics, information retrieval, data mining and image analysis. This work presents a novel image clustering method called Partial Least Square image Clustering (PLSIC), which employs a one-against-all Partial Least Squares classifier to find image clusters with low redundancy (each cluster represents different visual concept) and high purity (two visual concepts should not be in the same cluster). The main goal of the proposed approach is to find groups of images in an arbitrary set of unlabeled images to convey well defined visual concepts. As a case study, we evaluate the PLSIC to the video summarization problem by means of experiments with 50 videos from various genres of the Open Video Project, comparing summaries generated by the PLSIC with other video summarization approaches found in the literature. A experimental evaluation demonstrates that the proposed method can produce very satisfactory results.

关键词： image Clustering Partial Least Squares Video Summarization Shot Sampling

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BMAX: a bag of features based method for image classification 28

BMAX: a bag of features based method for image classificatio...

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28th SIBGRAPI Conference on graphics, Patterns and images SIBGRAPI

作者： Senna, Pedro Drummond, Isabela Neves Bastos, Guilherme Sousa Univ Fed Itajuba Inst Engn Sistemas & Tecnol Informacao Itajuba MG Brazil Univ Fed Itajuba Inst Matemat & Computacao Itajuba MG Brazil

ISBN: (纸本)9781467379625

This work presents an image classification method based on bag of features, that needs less local features extracted for create a representative description of the image. The feature vector creation process of our approach is inspired in the cortex-like mechanisms used in "Hierarchical Model and X" proposed by Riesenhuber & Poggio. Bag of Max Features - BMAX works with the distance from each visual word to its nearest feature found in the image, instead of occurrence frequency of each word. The motivation to reduce the amount of features used is to obtain a better relation between recognition rate and computational cost. We perform tests in three public images databases generally used as benchmark, and varying the quantity of features extracted. The proposed method can spend up to 60 times less local features than the standard bag of features, with estimate loss around 5% considering recognition rate, that represents up to 17 times reduction in the running time.

关键词： image classification bag-of-features HMAX low feature usage

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A Graph-Based Approach for Contextual image Segmentation

A Graph-Based Approach for Contextual Image Segmentation

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Gustavo B. Souza Gabriel M. Alves Alexandre L. M. Levada Paulo E. Cruvinel Aparecido N. Marana Universidade Federal de Sao Carlos Sao Carlos SP BR Embrapa Instrumentação Universidade Federal de São Carlos Universidade Estadual Paulista

ISBN: (纸本)9781509035694;9781509035687

image segmentation is one of the most important tasks in image Analysis since it allows locating the relevant regions of the images and discarding irrelevant information. Any mistake during this phase may cause serious problems to the subsequent methods of the image-based systems. The segmentation process is usually very complex since most of the images present some kind of noise. In this work, two techniques are combined to deal with such problem: one derived from the graph theory and other from the anisotropic filtering methods, both emphasizing the use of contextual information in order to classify each pixel in the image with higher precision. Given a noisy grayscale image, an anisotropic diffusion filter is applied in order to smooth the interior regions of the image, eliminating noise without loosing much information of boundary areas. After that, a graph is built based on the pixels of the obtained diffused image, linking adjacent nodes (pixels) and considering the capacity of the edges as a function of the filter properties. Then, after applying the Ford-Fulkerson algorithm, the minimum cut of the graph is found (following the min cut-max flow theorem), segmenting the object of interest. The results show that the proposed approach outperforms the traditional and well-referenced Otsu's method.

关键词： image segmentation image edge detection Gray-scale Anisotropic magnetoresistance Graph theory Noise measurement image analysis

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