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Factors Influencing the Perception of Realism in Synthetic Facial Expressions

Factors Influencing the Perception of Realism in Synthetic F...

引用

brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Rafael Luiz Testa Ariane Machado Lima Fátima de Lourdes dos Santos Nunes School of Arts Sciences and Humanities of the University São Paulo São Paulo Brazil Escola Politecnica of the University of São Paulo São Paulo Brazil

One way to synthesize facial expressions is to change an image to represent the desired emotion and it is useful in entertainment, diagnostic and psychiatric disorders therapy applications. Despite several existing approaches, there is little discussion about factors that contribute or hinder the perception of realism in synthetic facial expressions images. After presenting an approach for facial expressions synthesis through the deformation of facial features, this paper provides an evaluation by 155 volunteers regarding the realism of synthesized images. The proposed facial expression synthesis aims to generate new images using two source images (neutral and expressive face) and changing the expression in a target image (neutral face). The results suggest that assignment of realism depends on the type of image (real or synthetic). However, the synthesis presents images that can be considered realistic, especially for the expression of happiness. Finally, while factors such as color difference between subsequent regions and unnatural-sized facial features contribute to less realism, other factors such as the presence of wrinkles contribute to a greater assignment of realism to images.

关键词： Face Databases Facial features strain image reconstruction Feature extraction Visualization

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Single-Shot Person Re-Identification Combining Similarity Metrics and Support Vectors

Single-Shot Person Re-Identification Combining Similarity Me...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Anderson Luís Cavalcanti Sales Rafael Henrique Vareto William Robson Schwartz Guillermo Camara Chavez Universidade Federal de Ouro Preto Ouro Preto Minas Gerais Brazil Department of Computer Science Universidade Federal de Minas Gerais Brazil

Person Re-Identification is all about determining a person's entire course as s/he walks around camera-equipped zones. More precisely, person Re-ID is the problem of matching human identities captured from non-overlapping surveillance cameras. In this work, we propose an approach that learns a new low-dimensional metric space in an attempt to cut down multi-camera matching errors. We represent the training and test samples by concatenating handcrafted features. Then, the method performs a two-step ranking using elementary distance metrics and followed by an ensemble of weighted binary classifiers. We validate our approach on CUHK01 and PRID450s datasets, providing only a sample per class for probe and only a sample for gallery (single-shot). According to the experiments, our method achieves CMC Rank-1 results up to 61.1 and 75.4, following leading literature protocols, for CUHK01 and PRID450s, respectively.

关键词： Cameras Measurement Probes image color analysis Surveillance Feature extraction Support vector machines

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Color Quantization in Transfer Learning and Noisy Scenarios: An Empirical Analysis Using Convolutional Networks

Color Quantization in Transfer Learning and Noisy Scenarios:...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Tiago Santana de Nazare Gabriel de Barros Paranhos da Costa Rodrigo Fernandes de Mello Moacir Antonelli Ponti ICMC University of São Paulo São Carlos Brazil

Transfer learning is seen as one of the most promising areas of machine learning. Lately, features from pre-trained models have been used to achieve state-of-the-art results in several machine vision problems. Those models are usually employed when the problem of interest does not have enough supervised examples to support the network training from scratch. Most applications use networks pre-trained on noise-free RGB image datasets, what is observed even when the target domain counts on grayscale images or when data is degraded by noise. In this paper, we evaluate the use of Convolutional Neural Networks (CNNs) on such transfer learning scenarios and the impact of using RGB trained networks on grayscale image tasks. Our results confirm that the use of networks trained using colored images on grayscale tasks hinders the overall performance when compared to a similar network trained on a quantized version of the original dataset. Results also show that higher quantization levels (resulting in less colors) increase the robustness of CNN features in the presence of noise.

关键词： Feature extraction image color analysis Gray-scale Training Quantization (signal) Colored noise Convolutional codes

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Unsupervised Representation Learning Using Convolutional and stacked Auto-Encoders: A Domain and Cross-Domain Feature Space Analysis

Unsupervised Representation Learning Using Convolutional and...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Gabriel B. Cavallari Leonardo S.F. Ribeiro Moacir A. Ponti Universidade de Sao Paulo Sao Paulo SÃ£o Paulo BR

A feature learning task involves training models that are capable of inferring good representations (transformations of the original space) from input data alone. When working with limited or unlabelled data, and also when multiple visual domains are considered, methods that rely on large annotated datasets, such as Convolutional Neural Networks (CNNs), cannot be employed. In this paper we investigate different auto-encoder (AE) architectures, which require no labels, and explore training strategies to learn representations from images. The models are evaluated considering both the reconstruction error of the images and the feature spaces in terms of their discriminative power. We study the role of dense and convolutional layers on the results, as well as the depth and capacity of the networks, since those are shown to affect both the dimensionality reduction and the capability of generalising for different visual domains. Classification results with AE features were as discriminative as pre-trained CNN features. Our findings can be used as guidelines for the design of unsupervised representation learning methods within and across domains.

关键词： Feature extraction Decoding Training Convolutional codes image reconstruction Visualization Task analysis

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Hidden Surface Removal for Accurate Painting-Area Calculation on CAD Models

Hidden Surface Removal for Accurate Painting-Area Calculatio...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Lucas Figueiredo Paulo Ivson Waldemar Celes Computer Science Department and Tecgraf Institute Pontifical Catholic University of Rio de Janeiro - PUC-Rio Rio de Janeiro Brasil

3D CAD models are widely used to improve management of large-scale engineering projects. Examples include Building Information Modeling (BIM) and Oil & Gas industrial plants. Maintaining these facilities is a critical task that often involves anti-corrosive painting of equipment and metallic structures. Existing CAD software estimates the painting area including hidden surfaces that are not actually painted in the field. To improve these computations, we propose an approach based on Adaptively-Sampled Distance Fields (ADFs) exploiting the relationship between object areas and Constructive Solid Geometry (CSG) operations. Tests with synthetic models demonstrate that our technique achieves an accuracy of 99%. In real-world 3D CAD models, we were able to reduce the estimated area by 38% when compared to the naïve calculations. These result in significant cost savings in material provision and workforce required for maintaining these facilities.

关键词： Solid modeling Painting Computational modeling Geometry Three-dimensional displays Surface cracks

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A Novel Fingerprint Quality Assessment Based on Gabor Filters

A Novel Fingerprint Quality Assessment Based on Gabor Filter...

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brazilian symposium on computer graphics and image processing (SIBGRAPI)

作者： Igor Lucena Peixoto Andrezza João Janduy Brasileiro Primo Erick Vagner Cabral de Lima Borges Arnaldo Gualberto de Andrade e Silva Leonardo Vidal Batista Herman Martins Gomes Vsoft Tecnologia João Pessoa-PB Brazil Federal University of Campina Grande Campina Grande-PB Brazil Federal University of Paraiba João Pessoa-PB Brazil

Fingerprints are the most widely deployed biometric characteristics. However, the recognition of a fingerprint may be influenced by a lot of factors (e.g., skin conditions, sensor conditions) and a matching algorithm is highly affected by the quality of the images involved. This work proposes a novel method for Fingerprint Quality Assessment (FQA) based on the analysis of the Gabor filters response on a fingerprint image. The correlation between the worst quality templates and the matching score has also been analyzed. The method is validated on FVC2000DB3, FVC2004DB2, FVC2004DB3, and FVC2006DB3 databases. This work was compared to other FQAs in order to evaluate performance and with different matching algorithms for fair comparison. The results found pointed that the proposed method is able to identify the images which most affect the error rates of an AFIS, better than the other methods presented in the literature.

关键词： Fingerprint recognition Quality assessment Databases standards Histograms Forensics image recognition

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Toward a Robust System to Monitor Head Motions during PET Based on Facial Landmark Detection: A New Approach

Toward a Robust System to Monitor Head Motions during PET Ba...

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Annual IEEE symposium on computer-Based Medical Systems

作者： Sergey Anishchenko Vladislav Osinov Dmitry Shaposhnikov Lubov Podlachikova Richard Comley Xiaohong W. Gao A.B.Kogan Research Institute for Neurocybernetics Southern Federal University of Russia Russia School of Computing Science Middlesex University London UK

A new approach for the detection of head motions during PET scanning is presented. The proposed system includes 4 modules, which are: input module, face segmentation, facial landmark detection, and head movement estimation. The developed system is tested on pictures monitoring a subject's head while simulating PET scanning (n=12) and face images of subjects with different skin colours (n=31). Experimental results show that the centres of chosen facial landmarks (eye corners and middle point of nose basement) can be detected with high precision (1plusmn0.64 pixels). processing of 2D images with known moving parameters demonstrates that the parameter movement in terms of rotation and translation along X, Y, and Z directions can be obtained very accurately via the developed methods.

关键词： Robustness Monitoring Positron emission tomography Face detection Motion detection Head image segmentation System testing Skin Nose

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Development of an intuitive interface based on facial orientations and gazing actions for auto-wheel chair operation

Development of an intuitive interface based on facial orient...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Nobuaki Nakazawa Ilhwan Kim Takashi Mori Hiroki Murakawa Motohiro Kano Aya Maeda Toshikazu Matsui Kou Yamada Department of Production of Science and Technology Gunma University Oota Gunma Japan Department of Electrical and Electronic Engineering Kangwon University Chuncheon South Korea

This paper suggests an intuitive interface based on the facial orientations and gazing actions for auto-wheel chair operation. The real-time image of the operator's face was taken to the computer through the USB camera to observe the operational intention. The changes in the darkness area of the both nostrils were utilized for recognition of the face orientations. When the operator faced to up and downward, the darkness areas of both nostrils were increased and decreased, respectively. On the other hand, the difference between two nostril areas could be caused in cases where the face was turn to the side. Here, these characteristics were utilized for the recognition of the face orientations. Moreover, gazing actions was recognized by the curve ratio of the operator's eye lines. Only when the operator gazed to the control computer, the facial orientation was reflected to operate the auto-wheelchair, instead of a joystick interface.

关键词： Face Face recognition Brightness Universal Serial Bus Cameras image processing Cornea

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Real-Time Motion Feedback System based on Smart Mirror Vision

Real-Time Motion Feedback System based on Smart Mirror Visio...

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International symposium on Soft Computing and Intelligent Systems (SCIS)

作者： Seoungtak Kim Dasol Seo Sangyong Lee Yeonjun Kim Hyun Wook Kang Yong-Sik Choi Jin-Woo Jung Dongguk University Seoul Republic of Korea

ISBN: (数字)9781728197326

ISBN: (纸本)9781728197333

Modern people do not have much time to take care of their health due to heavy workloads. Therefore, we propose a smart mirror system, through which people can take exercises at home and get corrections for their movements. The users' motions are sent to the server using Raspberry Pi. Once the server receives the video, it sends the correct movements back to the user. Upon receiving the correct movements, the feedback, which is provided from the Guide video, the user can compare their movements to it. The users can correct their motions by following the correct motions provided from the Guide video. The incorrect motion is determined by the gap of the angle of the user's joints from the Guide video. This proposed Smart mirror system is assumed to contribute to people's health due to its ease of use and greater accessibility.

关键词： streaming media Servers Mirrors graphics processing units Real-time systems image color analysis computer science

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Efficient geometric graph matching using vertex embedding 13

Efficient geometric graph matching using vertex embedding

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21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, ACM SIGSPATIAL GIS 2013

作者： Armiti, Ayser Gertz, Michael Institute of Computer Science Heidelberg University Germany

ISBN: (纸本)9781450325219

For many applications such as road network analysis and image processing, it is critical to study spatial properties of objects in addition to object relationships. Geometric graphs provide a suitable modeling framework for such applications, where vertices are located in some 2D space. For applications where the similarity between the structures of different graphs plays an important role, typically, inexact graph matching algorithms are employed. However, graph matching algorithms face many problems such as scalability with respect to graph size and less tolerance to changes in graph structure or labels. In this paper, we propose a solution to the problem of inexact graph matching for geometric graphs in the 2D space. Our approach allows to effectively answer subgraph and common subgraph queries for geometric graphs that differ in structure, spatial properties, and labels. Initially, a spatial feature is extracted from each vertex, and string edit distance is used to find the distance between pairs of vertices. To speed up graph matching, we propose vertex embedding into the Euclidean space. Based on this, the distance between two vertices can be computed using the Euclidean distance in constant time. To answer subgraph and common subgraph queries, we introduce an iterative matching algorithm that matches two graphs using their similarity in the Euclidean space. Such an algorithm merges highly similar vertices to create similar connected subgraphs. Using representative geometric graphs extracted from road networks, we show that our approach outperforms existing graph matching approaches in terms of matching quality and runtime. © 2013 ACM.

关键词： Graphic methods

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