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检索条件"任意字段=Brazilian Symposium on Computer Graphics and Image Processing"

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Streaming Graph-Based Hierarchical Video Segmentation by a Simple Label Propagation

Streaming Graph-Based Hierarchical Video Segmentation by a S...

引用

brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Kleber J.F. de Souza Arnaldo de A. Araújo Silvio J.F. Guimarães Zenilton K.G. do Patrocínio Matthieu Cord DCC UFMG Belo Horizonte Brazil VIPLAB PUC Minas Belo Horizonte Brazil LIP6 Sorbonne Universités Paris France

In this paper, we present an approach to streaming graph-based hierarchical video segmentation by simple label propagation. Here, we transform the streaming video segmentation into a graph partitioning problem in which each part corresponds to one region of the video, furthermore, we apply a simple method for merging the segmentations of two consecutive blocks to achieve the temporal coherence. The spatial-temporal coherence is given, only, by color information instead of more complex features. We provide an extensive comparative analysis among our method and methods in the literature showing efficiency, ease of use, and temporal coherence of ours. According to the experiments, our method produces good results when applied to video segmentation besides presenting a low space and time cost, compared to other methods.

关键词： Streaming media Coherence Yttrium Logic gates Merging Three-dimensional displays image segmentation

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An Approach to Iris Contact Lens Detection Based on Deep image Representations

An Approach to Iris Contact Lens Detection Based on Deep Ima...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Pedro Silva Eduardo Luz Rafael Baeta Helio Pedrini Alexandre Xavier Falcao David Menotti Computing Department UFQP Ouro Preto MG Brazil Institute of Computing University of Campinas - UNICAMP Campinas SP Brazil

Spoofing detection is a challenging task in biometric systems, when differentiating illegitimate users from genuine ones. Although iris scans are far more inclusive than fingerprints, and also more precise for person authentication, iris recognition systems are vulnerable to spoofing via textured cosmetic contact lenses. Iris spoofing detection is also referred to as liveness detection (binary classification of fake and real images). In this work, we focus on a three-class detection problem: images with textured (colored) contact lenses, soft contact lenses, and no lenses. Our approach uses a convolutional network to build a deep image representation and an additional fully-connected single layer with soft max regression for classification. Experiments are conducted in comparison with a state-of-the-art approach (SOTA) on two public iris image databases for contact lens detection: 2013 Notre Dame and IIIT-Delhi. Our approach can achieve a 30% performance gain over SOTA on the former database (from 80% to 86%) and comparable results on the latter. Since IIIT-Delhi does not provide segmented iris images and, differently from SOTA, our approach does not segment the iris yet, we conclude that these are very promising results.

关键词： Lenses Iris recognition Databases Iris Training Network topology image representation

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Real-Time Local Unfolding for Agents Navigation on Arbitrary Surfaces

Real-Time Local Unfolding for Agents Navigation on Arbitrary...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Iago U. Berndt Rafael P. Torchelsen Anderson Maciel Instituto de Informtica (INF) Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil Centro de Desenvolvimento Tecnolgico (CDTec) Federal University of Pelotas (UFPel) Pelotas Brazil

Agents path planning is an essential part of games and crowd simulations. In those contexts they are usually restricted to planar surfaces due to the huge computational cost of mapping arbitrary surfaces to a plane without distortions. Mapping is required to benefit from the lower computational cost of distance calculations on a plane (Euclidean distance) when compared to distances on arbitrary surfaces (Geodesic distance). Although solutions have been presented, none have properly handled non-planar surfaces around the agent. In this paper we present mesh parametrization techniques to unfold the region around the agent allowing to extend to arbitrary surfaces the use of existing path planning algorithms initially designed only for planar surfaces. To mitigate the high computational cost of unfolding the entire surface dynamically, we propose pre-processing stages and massive parallelization, resulting in performances similar to that of using a planar surface. We also present a GPU implementation schema that permits a solution to be computed in real-time allowing agents to navigate on deformable surfaces that require dynamic unfolding of the surface. We present results with over 100k agents to prove the approach practicality.

关键词： Path planning Collision avoidance Navigation Computational efficiency graphics processing units Distortion Real-time systems

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Finger Spelling Recognition Using Kernel Descriptors and Depth images

Finger Spelling Recognition Using Kernel Descriptors and Dep...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： K. Otiniano-Rodríguez E. Cayllahua-Cahuina A. Araújo de A. G. Cámara-Chávez Department of Computer Science Federal University of Minas Gerais Belo Horizonte Brazil Universidade Federal de Minas Gerais Belo Horizonte MG BR Department of Computer Science Federal University of Ouro Preto Ouro Preto Brazil

Deaf people use systems of communication based on sign language and finger spelling. Finger spelling is a system where each letter of the alphabet is represented by a unique and discrete movement of the hand. RGB and depth images can be used to characterize hand shapes corresponding to letters of the alphabet. There exists an advantage of depth sensors, as Kinect, over color cameras for finger spelling recognition: depth images provide 3D information of the hand. In this paper, we propose a model for finger spelling recognition based on depth information using kernel descriptors, consisting of four stages. The performance of this approach is evaluated on a dataset of real images of the American Sign Language finger spelling. Different experiments were performed using a combination of both descriptors over depth information. Our approach obtains 92.92% of mean accuracy with 50% of samples for training, outperforming other state-of-the-art methods.

关键词： Kernel Accuracy Training Feature extraction Assistive technology Gesture recognition Shape

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An Embedded System for Aerial image processing from Unmanned Aerial Vehicles

An Embedded System for Aerial Image Processing from Unmanned...

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brazilian symposium on Computing System Engineering (SBESC)

作者： Jonas Fernandes da Silva Alisson V. Brito Jose Antonio Gomes De Lima Helder Nogueira De Moura Centro de Informática Cidade Universitaria Joao Pessoa PB Brasil Centro de Inf. Universidade Federal da Paraiba Joao Pessoa PB BR REINTEGRIS Cidade Univ. João Pessoa Brazil

This paper proposes solution capable to process aerial images from UAVs to identify failures in plantations and makes a comparison of the system running on light sized computers and low power computing platforms. An algorithm was developed based on watersheds using OpenCV library. The solution was embedded on X86 architecture (AlteraDE2i-150) and Intel Edison boards as well as on ARM architecture (Raspberry Pi 2). The results show that the proposed system is a cost-effective solution for the problem of fault identification in plantations, and can be embedded in UAVs for processing images in real time.

关键词： Power demand Embedded systems computer architecture Real-time systems Monitoring image segmentation

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Finger Spelling Recognition from Depth Data Using Direction Cosines and Histogram of Cumulative Magnitudes

Finger Spelling Recognition from Depth Data Using Direction ...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Edwin Escobedo Guillermo Camara Federal University of Ouro Preto Ouro Preto MG BR

In this paper, we propose a new approach for finger spelling recognition using depth information captured by Kinect sensor. We only use depth information to characterize hand configurations corresponding to alphabet letters. First, we use depth data to generate a binary hand mask which is used to segment the hand area from background. Then, the major hand axis is determined and aligned with Y axis in order to achieve rotation invariance. Later, we convert the depth data in a 3D point cloud. The point cloud is divided into sub regions and in each one, using direction cosines, we calculated three histograms of cumulative magnitudes Hx, Hy and Hz corresponding to each axis. Finally, these histograms were concatenated and used as input to our Support Vector Machine (SVM) classifier. The performance of this approach is quantitatively and qualitatively evaluated on a dataset of real images of American Sign Language (ASL) hand shapes. The dataset used is composed of 60000 depth images. According to our experiments, our approach has an accuracy rate of 99.37%, outperforming other state-of-the-art methods.

关键词： Histograms Assistive technology Three-dimensional displays Gesture recognition Support vector machines Accuracy image segmentation

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Improved Head-Shoulder Human Contour Estimation through Clusters of Learned Shape Models

Improved Head-Shoulder Human Contour Estimation through Clus...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Julio Cezar Silveira Jacques Soraia Raupp Musse Pontificia Universidade Catolica do Rio Grande do Sul Porto Alegre RS BR PUCRS Faculdade de Informática Porto Alegre Brazil

In this paper we propose a clustering-based learning approach to improve an existing model for human head-shoulder contour estimation. The contour estimation is guided by a learned head-shoulder shape model, initialized automatically by a face detector. A dataset with labeled data is used to create the head-shoulder shape model and to quantitatively analyze the results. In the proposed approach, geometric features are firstly extracted from the learning dataset. Then, the number of shape models to be learned is obtained by an unsupervised clustering algorithm. In the segmentation stage, different graphs with an omega-like shape are built around the detected face, related to each learned shape model. A path with maximal cost, related to each graph, defines a initial estimative of the head-shoulder contour. The final estimation is given by the path with maximum average energy. Experimental results indicate that the proposed technique outperformed the original model, which is based on a single shape model, learned in a more simple way. In addition, it achieved comparable accuracy to other state-of-the-art models.

关键词： Shape Feature extraction Computational modeling Face Estimation Neck image segmentation

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Dealing with frame cancellation for stereoscopic displays in 3D user interfaces 10

Dealing with frame cancellation for stereoscopic displays in...

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2015 10th IEEE symposium on 3D User Interfaces, 3DUI 2015

作者： Lacoche, Jérémy Le Chénéchal, Morgan Chalmé, Sébastien Royan, Jérôme Duval, Thierry Gouranton, Valérie Maisel, Eric Arnaldi, Bruno IRT B Com France Télécom Bretagne France INSA de Rennes France ENIB France

ISBN: (纸本)9781467368865

This paper aims at reducing the ocular discomfort created by stereoscopy due to the effect called 'frame cancellation', for movies and interactive applications. This effect appears when a virtual object in negative parallax (front of the screen) is clipped by the screen edges;stereopsis cue lets observers perceive the object popping-out from the screen while occlusion cue provides observers with an opposite signal. Such a situation is not possible in the real world. This explains some visual discomfort for observers and leads to a poor depth perception of the scene. This issue is directly linked to the physical limitations of the display size that may not cover the entire field of view of the observer. To deal with these physical constraints we introduce two new methods in the context of interactive applications. The first method consists in two new rendering effects based on progressive transparency that aim to preserve the popping-out effect of the stereo. The second method focuses on adapting the interaction of the user, not allowing him to place virtual objects in an area subject to frame cancellation. Both methods have been evaluated and have shown a good efficiency in comparison to the state of the art approaches. © 2015 IEEE.

关键词： Stereo image processing

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A quantitative cross-architecture study of morphological image processing on CPUs, GPUs, and FPGAs

A quantitative cross-architecture study of morphological ima...

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International Conference on computer Applications and Industrial Electronics (ICCAIE)

作者： Christian Brugger Lorenzo Dal'Aqua Javier Alejandro Varela Christian De Schryver Mohammadsadegh Sadri Norbert Wehn Martin Klein Michael Siegrist Microelectronic Systems Design Research Group University of Kaiserslautern Germany Technische Universitat Kaiserslautern Kaiserslautern Rheinland-Pfalz DE Wipotec Wiege-und Positioniersysteme GmbH Kaiserslautern Germany

The rapidly growing applications based on morphological operations in image processing and computer vision make efficient implementations of these key blocks an important topic of research. Nevertheless, a detailed comparison of the energy efficiency and performance of these implementations that covers all available major hardware platforms is still missing. In this paper we evaluate the performance and power consumption of the most efficient available morphological image processing algorithms for CPU, GPU, and FPGA platforms in detail. In addition, we study the suitability of available morphological library units for high-level synthesis and compare the results with an optimized hand-coded FPGA implementation. We demonstrate that even high-end GPUs cannot achieve the throughputs of modern CPUs and FPGAs by far. Our experimental results show that an FPGA implementation is 8-10 times more energy efficient for this application, being comparable in speed to CPUs for large kernels.

关键词： Field programmable gate arrays graphics processing units Libraries Kernel Hardware computer architecture image processing

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Parallel Implementation of OpenVX on Firefly2 GPU

Parallel Implementation of OpenVX on Firefly2 GPU

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International symposium on Computational Intelligence and Design, ISCID

作者： Zhiquan Guo Jungang Han Fang Che Tao Li School of Computer Science Xi'An University of Posts and Telecommunications Xi'An China School of Electronic Engineering Xi’ An University of Posts and Telecommunications Xi’ An China

ISBN: (纸本)9781467395885

Given the fact that the traditional GPU mainly supports the parallel computing with SIMD (Single Instruction Multiple Data) and SIMT (Single Instruction Multiple Thread) mode, the Firefly2 GPU (Graphic processing Unit) has special hardware configuration mechanism and can be used for paralleling computing on data-level, thread-level and operated-level. This paper presents parallel implementation of OpenVX kernels on Firefly2 GPU with the method by combing the operation level parallelism with data level parallelism. Experimental results indicate satisfactory speedup of the parallel implementation and show that the Firefly2 is suitable for graphics and image processing.

关键词： Parallel processing graphics processing units Hardware Kernel Machine vision Partitioning algorithms

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