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Emotion recognition from thermal infrared images using deep Boltzmann machine

Frontiers of computer science 2014年第4期8卷 609-618页

作者： Shangfei WANG Menghua HE Zhen GAO Shan HE Qiang JI School of Computer Science and Technology University of Science and Technology of China Hefei 230027 China Key Lab of Computing and Communicating Software of Anhui Province Hefei 230027 China Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY 12180-3590 USA

Facial expression and emotion recognition from thermal infrared images has attracted more and more attentions in recent years. However, the features adopted in current work are either temperature statistical parameters extracted from the facial regions of interest or several hand-crafted features that are commonly used in visible spectrum. Till now there are no image features specially designed for thermal infrared images. In this paper, we propose using the deep Boltzmann machine to learn thermal features for emotion recognition from thermal infrared facial images. First, the face is located and normalized from the thermal infrared im- ages. Then, a deep Boltzmann machine model composed of two layers is trained. The parameters of the deep Boltzmann machine model are further fine-tuned for emotion recognition after pre-tralning of feature learning. Comparative experimental results on the NVIE database demonstrate that our approach outperforms other approaches using temperature statistic features or hand-crafted features borrowed from visible domain. The learned features from the forehead, eye, and mouth are more effective for discriminating valence dimension of emotion than other facial areas. In addition, our study shows that adding unlabeled data from other database during training can also improve feature learning performance.

关键词： emotion recognition thermal infrared images deep Boltzmann machine

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New identity-based key-encapsulation mechanism and its applications in cloud computing

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International Journal of High Performance Computing and Networking 2015年第2期8卷 124-134页

作者： Wang, Hao Zheng, Zhihua Yang, Bo School of Information Science and Engineering Shandong Normal University Jinan Shandong250014 China Shandong Provincial Key Laboratory for Novel Distributed Computer Software Technology Jinan Shandong250014 China Shandong Provincial Key Laboratory of Software Engineering Jinan Shandong250101 China Department of Electronic Engineering Yantai Vocational College Yantai Shandong264670 China

Identity-based encryption (IBE) is an important primitive of identity-based cryptography. As such, it is a type of public-key encryption in which the public key of a user is some unique information about the identity of the user (e.g., a user's e-mail address). As a special form of IBE, identity-based key encapsulation mechanism (IB-KEM) can be used to create a random session key for encrypting messages. Any IB-KEM can be updated to a full IBE scheme by adding a symmetric encryption scheme with appropriate security properties. Currently, IB-KEM is a fundamental primitive of cryptography, and can be used to protect information system security, network security, cloud security, etc. In this paper, we construct a new IB-KEM in a generic levelled multilinear map setting and prove its security under multilinear decisional Diffie-Hellman assumption in the selective-ID model. Then, we make our IB-KEM translated to the GGH framework, which is proposed by Garg et al. (2013a). This framework defines an approximate version of a multilinear group family from ideal lattices. Finally, as an application of our new scheme, we introduce how to achieve secure transmission in the hierarchical architecture for cloud computing (HACC). Copyright © 2015 Inderscience Enterprises Ltd.

关键词： Cloud computing

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Fusion of visible and thermal images for facial expression recognition

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Frontiers of computer science 2014年第2期8卷 232-242页

作者： Shangfei WANG Shan HE Yue WU Menghua HE Qiang JI School of Computer Science and Technology University of Science and Technology of China Hefei 230027 China Key Lab of Computing and Communicating Software of Anhui Province Hefei 230027 China Department of Electrical Computer and Systems Engineering Rensselaer Polytechnic Institute Troy NY12180-3590 USA

Most present research into facial expression recognition focuses on the visible spectrum, which is sen- sitive to illumination change. In this paper, we focus on in- tegrating thermal infrared data with visible spectrum images for spontaneous facial expression recognition. First, the ac- tive appearance model AAM parameters and three defined head motion features are extracted from visible spectrum im- ages, and several thermal statistical features are extracted from infrared （IR） images. Second, feature selection is per- formed using the F-test statistic. Third, Bayesian networks BNs and support vector machines SVMs are proposed for both decision-level and feature-level fusion. Experiments on the natural visible and infrared facial expression （NVIE） spontaneous database show the effectiveness of the proposed methods, and demonstrate thermal 1R images＇ supplementary role for visible facial expression recognition.

关键词： facial expression recognition feature-level fu-sion decision-level fusion support vector machine Bayesiannetwork thermal infrared images visible spectrum images

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CIRM: A candidate item reduce method on mapreduce for meteorological big data application

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Energy Education science and technology Part A: Energy science and Research 2014年第6期32卷 6209-6220页

作者： Xue, Shengjun Huang, Junsheng Xu, Xiaolong Zhang, Jie Jing, Lu Nanjing University of Information Science and Technology School of Computer and Software Nanjing China Nanjing University of Information Science and Technology Jiangsu Engineering Center of Network Monitoring Nanjing China Nanjing University State Key Laboratory for Novel Software Technology Nanjing China Nanjing University Department of Computer Science and Technology Nanjing China Shanghai Meteorological Information and Technical Support Centre Shanghai China Computer Science Department Oklahoma State University StillwaterOK United States

With the increase of the number of meteorological stations, the meteorological data is growing rapidly. Association analysis algorithm is widely applied to the analysis of meteorological data. The traditional association analysis algorithm is difficult to meet the needs of meteorological big data processing. In order to solve this problem, in this paper, we propose a candidate item reduce method named CIRM. It aims at reducing the times of searching data sets and the number of generating candidate sets. To improve its scalability and efficiency in big data environment, CIRM is implemented on Hadoop, a widely-adopted distributed computing platform using the MapReduce parallel processing paradigm. Finally, extensive experiments are conducted on meteorological data sets, and results demonstrate that CIRM significantly improves the efficiency and scalability of the Meteorological analysis data over existing approaches. © Sila science. All rights reserved.

关键词： MapReduce

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GAIN: GPU-based constraint checking for context consistency 21

GAIN: GPU-based constraint checking for context consistency

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21st Asia-Pacific software Engineering Conference, APSEC 2014

作者： Sui, Jun Xu, Chang Xi, Wang Jiang, Yanyan Cao, Chun Ma, Xiaoxin Lu, Jian State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Department of Computer Science and Technology Nanjing University Nanjing China

ISBN: (纸本)9781479974252

Applications in pervasive computing are often context-Aware. However, due to uncontrollable environmental noises, contexts collected by applications can be distorted or even conflicting with each other. This is known as the context inconsistency problem. To provide reliable services, applications need to validate contexts before using them. One promising approach is to check contexts against consistency constraints at the runtime of applications. However, this can bring heavy computations due to tremendous amounts of contexts, thus leading to deteriorated performance to applications. Previous work has proposed incremental or concurrent checking techniques to improve the checking performance, but they heavily rely on CPU computing. In this paper, we propose a novel technique GAIN to exploit GPU computing to improve the checking performance. GAIN can automatically recognize parallel units in a constraint and schedule their checking in parallel on GPU cores. We evaluated GAIN with various constraints under different workloads. Our evaluation results show that, compared to CPU-based computing, GAIN saves CPU computing resources for pervasive applications while checks constraints much more efficiently. © 2014 IEEE.

关键词： Ubiquitous computing

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SHAP: Suppressing the detection of inconsistency hazards by pattern learning 21

SHAP: Suppressing the detection of inconsistency hazards by ...

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21st Asia-Pacific software Engineering Conference, APSEC 2014

作者： Xi, Wang Xu, Chang Yang, Wenhua Yu, Ping Ma, Xiaoxing Lu, Jian State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Department of Computer Science and Technology Nanjing University Nanjing China

ISBN: (纸本)9781479974252

Context-Aware applications rely on contexts derived from sensory data to adapt their behavior. However, contexts can be inconsistent and cause application anomaly or crash. One popular solution is to detect and resolve context inconsistencies at runtime. However, we observe that many detected inconsistencies do not indicate real context problems. Instead, they are caused by improper inconsistency detection. These inconsistencies are harmless, and their resolution is unnecessary or may even cause new problems. We name them inconsistency hazards. Inconsistency hazards should be suppressed, but their occurrences resemble normal inconsistencies. In this paper, we present a pattern-learning based approach SHAP to suppressing the detection of inconsistency hazards. Our key insight is that the detection of such hazards is subject to certain patterns of context changes. These patterns, although difficult to specify manually, can be learned effectively from historical inconsistency detection data. We evaluated our SHAP experimentally through three context-Aware applications. The results reported that SHAP can automatically suppress the detection of over 90% inconsistency hazards, while preserving the detection of over 98% normal inconsistencies, with only negligible overhead. © 2014 IEEE.

关键词： Hazards

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Distributed stochastic ADMM for matrix factorization 14

Distributed stochastic ADMM for matrix factorization

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23rd ACM International Conference on Information and Knowledge Management, CIKM 2014

作者： Yu, Zhi-Qin Shi, Xing-Jian Yan, Ling Li, Wu-Jun Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and Engineering Shanghai Jiao Tong University China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong National Key Laboratory for Novel Software Technology Department of Computer Science and Technology Nanjing University China

ISBN: (纸本)9781450325981

Matrix factorization (MF) has become the most popular technique for recommender systems due to its promising performance. Recently, distributed (parallel) MF models have received much attention from researchers of big data community. In this paper, we propose a novel model, called distributed stochastic alternating direction methods of multipliers (DS-ADMM), for large-scale MF problems. DS-ADMM is a distributed stochastic variant of ADMM. In particular, we first devise a new data split strategy to make the distributed MF problem fit for the ADMM framework. Then, a stochastic ADMM scheme is designed for learning. Finally, we implement DS-ADMM based on message passing interface (MPI), which can run on clusters with multiple machines (nodes). Experiments on several data sets from recommendation applications show that our DS-ADMM model can outperform other state-of-the-art distributed MF models in terms of both efficiency and accuracy. Copyright 2014 ACM.

关键词： Recommender systems

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Album quickview in comic-like layout via quartet analysis 22

Album quickview in comic-like layout via quartet analysis

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22nd Pacific Conference on computer Graphics and Applications, PG 2014

作者： Zheng, Zhibin Zhang, Yan Miao, Zheng Sun, Zhengxing State Key Lab for Novel Software Technology Nanjing University Jiangsu Nanjing210093 China Department of Computer Science and Technology Nanjing University Jiangsu Nanjing210093 China

ISBN: (纸本)9783905674736

For clear summary and efficient search of images for album, which carries a story of life record, we propose a new approach for quickview of album in comic-like layout via quartet analysis. How to organize the images in album and in what way to display images in collage are two key problems for album quickview. For the first problem, we take the idea of model organization method based on quartet analysis to construct categorization tree to organize the images;while for the second problem, we utilize the topological structure of categorization tree to decompose it into multiple groups of images and extract representative image from each group for subsequent collage. For the collage part, we choose comic-like layout to present collage because comic provides a concise way for storytelling and it has variablitiy in layout styles, which is suitable for album summary. Experiments demonstrate that our method could organize the images effectively and present images in collage with diverse styles as well. © The Eurographics Association 2014.

关键词： Topology

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Coupled group lasso for web-scale CTR prediction in display advertising 31

Coupled group lasso for web-scale CTR prediction in display ...

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31st International Conference on Machine Learning, ICML 2014

作者： Yan, Ling Li, Wu-Jun Xue, Gui-Rong Han, Dingyi Department of Computer Science and Engineering Shanghai Key Laboratory of Scalable Computing and Systems Shanghai Jiao Tong University China Department of Computer Science and Technology National Key Laboratory for Novel Software Technology Nanjing University China Alibaba Group China

ISBN: (纸本)9781634393973

In display advertising, click through rate (CTR) prediction is the problem of estimating the probability that an advertisement (ad) is clicked when displayed to a user in a specific context. Due to its easy implementation and promising performance, logistic regression (LR) model has been widely used for CTR prediction, especially in industrial systems. However, it is not easy for LR to capture the nonlinear information, such as the conjunction information, from user features and ad features. In this paper, we propose a novel model, called coupled group lasso (CGL), for CTR prediction in display advertising. CGL can seamlessly integrate the conjunction information from user features and ad features for modeling. Furthermore, CGL can automatically eliminate useless features for both users and ads, which may facilitate fast online prediction. Scalability of CGL is ensured through feature hashing and distributed implementation. Experimental results on real-world data sets show that our CGL model can achieve state-of-the-art performance on web- scale CTR prediction tasks. Copyright © (2014) by the International Machine Learning Society (IMLS) All rights reserved.

关键词： Forecasting

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A GA-based approach for SQL-injection detection

A GA-based approach for SQL-injection detection

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2013 International Conference on Information Engineering, ICIE 2013

作者： Chen, Jianmin Yang, Lin Zhang, Honghao Liu, Yan College of Computer Science Beijing University of Technology Beijing China Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin China National Computer Virus Emergency Response Center Tianjin China

ISBN: (纸本)9781845648558

In order to deal with serious security threats of SQL injection to Web applications, this paper proposes a novel SQL-injection detection method based on genetic algorithm (GA). A unified description for characteristics of SQL-injection was issued by regular expression, and an optimized SQL-injection sequence motherboard was got through GA. We detected harmful levels of SQL-injection attacks using template matching and achieved optimized correction scheme of the algorithm by a large amount of data. © 2014 WIT Press.

关键词： Genetic algorithms

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