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Monocular 3D Facial Information Retrieval for Automated Facial Expression Analysis

Monocular 3D Facial Information Retrieval for Automated Faci...

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International Conference on Affective Computing and Intelligent Interaction

作者： Meshia Cedric Oveneke Isabel Gonzalez Weiyi Wang Dongmei Jiang Hichem Sahli VUB-NPU Joint AVSP Research Lab Vrije Universiteit Brussel (VUB) Deptartment of Electronics & Informatics (ETRO) VUB-NPU Joint AVSP Research Lab Northwestern Polytechnical University (NPU) Shaanxi Key Lab on Speech and Image Information Processing

ISBN: (纸本)9781479999545

Understanding social signals is a very important aspect of human communication and interaction and has therefore attracted increased attention from various research areas. Among the different types of social signals, particular attention has been paid to facial expression of emotions and its automated analysis from image sequences. Automated facial expression analysis is a very challenging task due to the complex three-dimensional deformation and motion of the face associated to the facial expressions and the loss of 3D information during the image formation process. As a consequence, retrieving 3D spatio-temporal facial information from image sequences is essential for automated facial expression analysis. In this paper, we propose a framework for retrieving three-dimensional facial structure, motion and spatio-temporal features from monocular image sequences. First, we estimate monocular 3D scene flow by retrieving the facial structure using shape-from-shading (SFS) and combine it with 2D optical flow. Secondly, based on the retrieved structure and motion of the face, we extract spatio-temporal features for automated facial expression analysis. Experimental results illustrate the potential of the proposed 3D facial information retrieval framework for facial expression analysis, i.e. facial expression recognition and facial action-unit recognition on a benchmark dataset. This paves the way for future research on monocular 3D facial expression analysis.

关键词： EXPRESSION ANALYSIS facial information Personal communication Face Facial Expression image sequences information retrieval Face Automation formation process

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A new approach to create 3D fixation density maps for stereoscopic images

A new approach to create 3D fixation density maps for stereo...

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3DTV Conference

作者： Baoyan Ma Jun Zhou Xiao Gu Mingmin Wang Ya Zhang Xiaoqiang Guo Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai China Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai NGB laboratories Co. LTD Shanghai China Academy of Broadcasting Science Beijing China

An approach to create fixation density maps(FDM) for stereoscopic images is proposed in this paper, overcoming the shortages of current methods. A new representation of stereoscopic images like Computed Tomography (CT) is used, which can show more information such as depth and discomfort zone. Apart from this, we follow the protogenetic 2D calibration of eyetracker by a 3D offline calibration to gain accuracy of 3D gaze points, tuned to a particular user. We combine these two parts through classifying eyetracking data to several depth planes which are segmented in the procedure of the representation method like CT, and obtain the fixation distribution in different depth levels for a stereoscopic image.

关键词： Three-dimensional displays Stereo image processing Calibration Frequency division multiplexing image segmentation Visualization Accuracy

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A depth map estimation approach for trinocular stereo

A depth map estimation approach for trinocular stereo

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IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB)

作者： Jun Zhou Ling Wang Xiao Gu Kang Xu Ya Zhang Shanghai Key Laboratory of Digital Media Processing and Transmissions Shanghai China Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Shanghai China Shanghai Media and Entertainment Technology Group Co. Ltd. Shanghai China

This paper presents an approach for dense depth estimation taking the input of a trinocular stereo. The approach works with a global energy minimization framework based on Markov Random Field models. The occlusion and spatial consistency constraints are explicitly considered in an iterative fashion. Depth maps are initialized by belief propagation using AD-Census metric, and then refined by Mean Shift Segments Fusion. We further incorporate the occlusion constraint for trinocular stereo to refine our depth map. In order to make the inference tractable, we implement our algorithm in an iterative scheme where the disparity map and occlusion map of each view are updated iteratively. Finally, three disparity maps corresponding to a trinocular stereo are estimated. Our approach addresses the problems such as untextured regions, occlusions, inconsistency in spatial region in a unified framework. The experimental results show our approach works well on trinocular stereo.

关键词： Silicon Integrated circuits image color analysis image segmentation Estimation Belief propagation Three-dimensional displays

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Investigating the stability of fast iterative shrinkage thresholding algorithm for MR imaging reconstruction using compressed sensing

Investigating the stability of fast iterative shrinkage thre...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Guishan Zhang Haitao Deng Yaowen Chen Zhiwei Shen Renhua Wu Key Lab. of Digital Signal and Image Processing of Guangdong Province Shantou University Shantou China Department of Medical Imaging 2nd Affiliated Hospital Medical College of Shantou University Shantou China

ISBN: (纸本)9781467376839

Compressed sensing (CS) has been applied to the field of sub-sampled magnetic resonance imaging (MRI) reconstruction (CS-MRI). Fast iterative shrinkage-thresholding algorithm (FISTA) is an effective method for CS-MR images reconstruction. To investigate the accuracy and efficiency of the proposed algorithm, we applied it to the under-sampling MR images gained by different MRI scanning sequences. We found the peak signal to noise ratio (PSNR) of reconstructed MRI with varying sampling ratios diminished from Axial T1 weighted images (Ax T1) (45.13±12.97 dB), Axial T2 weighted images (Ax T2) (42.8 ± 14.95 dB), FLAIR (41.74 ± 14.15 dB), Diffusion Weighted Imaging (DWI) (40.23 ±17.40 dB) and Sagittal T2 weighted images (Sag T2) (36.28±12.32 dB), but there was no significant difference among the groups. In addition, the changes to the elapsed time of them was minor, Ax T1 (1.09±0.13 s), Ax T2 (1.30±0.13s), FLAIR (1.02±0.12s), DWI (1.07±0.13s) and Sag T2 (1.12±0.07s). Our results confirmed the stability of the proposed fast MRI reconstruction method for different scanning sequences. Further efforts are still needed to design the clinical sequence with sub-sampled acquisition strategy which may be a developing technique with clinical value.

关键词： Compressed Sensing Magnetic Resonance Imaging PSNR Fast Iterative Shrinkage-thresholding Algorithm (FISTA)

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Indoor Localization with Incomplete Observation Using Set-membership Filter

Indoor Localization with Incomplete Observation Using Set-me...

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International Symposium on Micro-NanoMechatronics and Human Science

作者： Yuan Wang Jian Huang Key Lab of Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology

ISBN: (纸本)9781467382182

Indoor localization is a popular topic because of the poor performance of GPS in the indoor environment. This paper has provided a new method to achieve the goal of indoor localization. Combining the usage of posture sensors with the Radio Frequency Identification (RFID) technology, we solved the problem of plentiful tags in the traditional RFID indoor localization. The relative localization subsystem is based on posture sensors and the absolute localization subsystem is based on RFID. A set-membership theory based data fusion algorithm is proposed to fuse the data of relative localization and absolute localization. Experimental results show that the proposed data fusion algorithm could significantly reduce the accumulated error of our indoor localization system.

关键词： Ellipsoids Indoor environments RFID tags Filtering theory Filtering algorithms

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Multimodal depression recognition with dynamic visual and audio cues

Multimodal depression recognition with dynamic visual and au...

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International Conference on Affective Computing and Intelligent Interaction and Workshops, ACII

作者： Lang He Dongmei Jiang Hichem Sahli NPU-VUB Joint AVSP Research lab Shaanxi Key Lab on Speech and Image Information Processing Xi'an China Deptartment of Electronics & Informatics(ETRO) Vrije Universiteit Brussel(VUB) Brussels Belgium Interuniversity Microelectronics Centre(IMEC) Heverlee Belgium

In this paper, we present our system design for audio visual multi-modal depression recognition. To improve the estimation accuracy of the Beck Depression Inventory (BDI) score, besides the Low Level Descriptors (LLD) features and the Local Gabor Binary Pattern-Three Orthogonal Planes (LGBP-TOP) features provided by the 2014 Audio/Visual Emotion Challenge and Workshop (AVEC2014), we extract extra features to capture key behavioural changes associated with depression. From audio we extract the speaking rate, and from video, the head pose features, the Space-Temporal Interesting Point (STIP) features, and local kinematic features via the Divergence-Curl-Shear descriptors. These features describe body movements, and spatio-temporal changes within the image sequence. We also consider global dynamic features, obtained using motion history histogram (MHH), bag of words (BOW) features and vector of local aggregated descriptors (VLAD). To capture the complementary information within the used features, we evaluate two fusion systems - the feature fusion scheme, and the model fusion scheme via local linear regression (LLR). Experiments are carried out on the training set and development set of the Depression Recognition Sub-Challenge (DSC) of AVEC2014, we obtain root mean square error (RMSE) of 7.6697, and mean absolute error (MAE) of 6.1683 on the development set, which are better or comparable with the state of the art results of the AVEC2014 challenge.

关键词： Feature extraction Visualization Speech Head Histograms Optical imaging History

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3D Emotional Facial Animation Synthesis with Factored Conditional Restricted Boltzmann Machines

3D Emotional Facial Animation Synthesis with Factored Condit...

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International Conference on Affective Computing and Intelligent Interaction

作者： Yong Zhao Dongmei Jiang Hichem Sahli NPU-VUB Joint AVSP Research Lab School of Computer Science Northwestern Polytechnical University (NPU) Shaanxi Key Lab on Speech and Image Information Processing NPU-VUB Joint AVSP Research Lab Vrije Universitiet Brussel (VUB) Department of Electronics & Informatics (ETRO)

ISBN: (纸本)9781479999545

This paper presents a 3D emotional facial animation synthesis approach based on the Factored Conditional Restricted Boltzmann Machines (FCRBM). Facial Action Parameters (FAPs) extracted from 2D face image sequences, are adopted to train the FCRBM model parameters. Based on the trained model, given an emotion label sequence and several initial frames of FAPs, the corresponding FAP sequence is generated via the Gibbs sampling, and then used to construct the MPEG-4 compliant 3D facial animation. Emotion recognition and subjective evaluation on the synthesized animations show that the proposed method can obtain natural facial animations representing well the dynamic process of emotions. Besides, facial animation with smooth emotion transitions can be obtained by blending the emotion labels.

关键词： Facial expression synthesis FCRBM FAP

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Compressive tracking moving cells in time-lapse image sequences

Compressive tracking moving cells in time-lapse image sequen...

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IEEE International Conference on Orange Technologies (ICOT)

作者： Chen Ding Ying Li Yongsheng Pan Tao Zhou Pengcheng Gao Yong Xia Center for Multidisciplinary Convergence Computing (CMCC) Northwestern Polytechnical University Xi'an China Shaanxi Key Lab of Speech & Image Information Processing (SAIIP) Northwestern Polytechnical University Xi'an China School of Science Ningxia Medical University Yinchuan China

ISBN: (纸本)9781467382380

Tracking the motion of cells in time-lapse image sequences plays a pivotal role in both research settings and clinical practices. In spite of their prevalence, automated cell tracking approaches are still facing several major challenges, including the effectiveness of cell detection, accuracy of tracking and high computational complexity. In this paper, we propose a segmentation-based compressive tracking (SBCT) algorithm for moving cells. This algorithm consists three major steps, including detecting the bounding box of each cell, extracting image features in each bounding box using compressive sensing, and identifying the correspondence between cells in adjacent frames using a trained naive Bayes classifier. The proposed SBCT algorithm has been evaluated against seven state-of-the-art cell tracking approaches on two time-lapse images sequences provided by the 2014 cell tracking challenge. Our results suggest that the proposed algorithm can successfully tracking moving cells with relatively high accuracy and low computational complexity.

关键词： Tracking image segmentation Feature extraction image sequences Classification algorithms Compressed sensing Shape

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Robust Multimodal Biometric Identification System Using Finger-Knuckle-Print features

Robust Multimodal Biometric Identification System Using Fing...

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International Conference on Control, Engineering & Information Technology

作者： Abdallah Meraoumia Salim Chitroub Ahmed Bouridane Univ Ouargla Fac. des nouvelles technologies de l'information et de la communication Lab. de Genie Electrique Signal and Image Processing Laboratory Electronics and Computer Science Faculty USTHB School of Computing Engineering and Information Sciences Northumbria University

ISBN: (纸本)9781479982134

Automatic personal identification is becoming an increasingly important requirement in a variety of applications like access control, surveillance systems and physical buildings. In recent years, biometric systems are used in these fields, offering greater convenience and several advantages over traditional security. In this paper, we propose an efficient online personal identification system based on Finger-Knuckle-Print (FKP) images. In this study, the finger image is characterized by the two dimensional Bloc based Discrete Cosine Transform (2D-BDCT) coefficients. Then, we use the Hidden Markov Model (HMM) for modeling the observation vector. In addition, the same finger is transformed by the two dimensional Discrete Fourier Transform (2D-DFT). The response of this transformation is directly used to create another observation vector. Subsequently, the two sub-systems are integrated in order to construct an efficient multi-modal identification system based on matching score level fusion. The results on a medium-size database, 150 users, show good identification performance based on individual modalities as well as after fusing multiple finger types.

关键词： Biometrics Identification FKP 2D-BDCT 2D-DFT HMM Data fusion

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Simple and effective image quality assessment based on edge enhanced mean square error

Simple and effective image quality assessment based on edge ...

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International Conference on Wireless communications and Signal processing (WCSP)

作者： Ziguan Cui Zongliang Gan Guijin Tang Feng Liu Xiuchang Zhu Image Processing & Image Communication Lab Nanjing University of Posts & Telecommunications Nanjing China

ISBN: (纸本)9781479973408

Simple and effective image quality assessment (IQA) method is very desirable in many image and video processing applications, such as coding, transmission, restoration and enhancement. Classic pixel absolute error based objective IQA metrics such as mean square error (MSE) and corresponding peak signal to noise ratio (PSNR) are widely used for various applications due to low computation and clear physical meanings, but have also been criticized for poorly correlated with subjective evaluation. Inspired by that human visual system (HVS) is more sensitive to image local edge distortion than flat or texture areas, in this paper, we propose a novel edge enhanced MSE (EE-MSE) to emphasize edge distortion effects on IQA. Experimental results on LIVE database release 2 show that the proposed EE-MSE IQA metric is competitive with state-of-the-art HVS-based IQA metrics, while has lower computational complexity and is more suitable for optimization task.

关键词： Measurement image quality image edge detection PSNR Visualization Complexity theory

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