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Evaluation of Motor Training Performance in 3D virtual Environment via Combining Brain-computer Interface and Haptic Feedback

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Procedia computer Science 2017年 107卷 256-261页

作者： Hong Wu Shuang Liang Wenlong Hang Xiaolu Liu Qiong Wang Kup-Sze Choi Jing Qin School of Information Engineering Wuhan University of Technology Wuhan 430070 China Shenzhen Key Laboratory of Virtual Reality and Human Interaction Technology Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen 518055 China School of Digital Media Jiangnan University Wuxi 214122 China School of Biomedical Engineering Shenzhen University Shenzhen 518060 China Department of Computer Science and Engineering The Chinese University of Hong Kong Shatin Hong Kong Centre for Smart Health School of Nursing The Hong Kong Polytechnic University Hung Hom Hong Kong

Brain-computer interfaces (BCIs) based on virtual reality (VR) mostly integrate visual and/or auditory feedback. Haptic feedbackwhich has the potential on improving the feasibility and operability of VR-based BCI systems is rarely explored in previous studies. In this article, we present a novel framework of BCI system based on both visual and haptic feedback, in which users can learn to manipulate the haptic device's stylus for motor training. The effects of motor training with and without haptic feedback are evaluated by detecting and analysing the changes of electroencephalogram (EEG). The preliminary experimental results indicate that haptic feedback may influence the modulation of the beta rhythms over left and right sensorimotor cortex during hand movements. This study can be easily replicated to evaluate the existing systems with haptic feedback and used to develop new applications for motor training.

关键词： Haptic feedback brain-computer interface (BCI) Electroencephalogram (EEG) event-related spectral perturbation (ERSP) virtual reality (VR)

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Robust object tracking using valid fragments selection 22nd

Robust object tracking using valid fragments selection

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22nd International Conference on MultiMedia Modeling, MMM 2016

作者： Zheng, Jin Li, Bo Tian, Peng Luo, Gang Beijing Key Laboratory of Digital Media School of Computer Science and Engineering Beihang University Beijing100191 China State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing100191 China Schepens Eye Research Institute Mass Eye and Ear Harvard Medical School BostonMA02114 United States

ISBN: (纸本)9783319276700

Local features are widely used in visual tracking to improve robustness in cases of partial occlusion, deformation and rotation. This paper proposes a local fragment-based object tracking algorithm. Unlike many existing fragment-based algorithms that allocate the weights to each fragment, this method firstly defines discrimination and uniqueness for local fragment, and builds an automatic pre-selection of useful fragments for tracking. Then, a Harris-SIFT filter is used to choose the current valid fragments, excluding occluded or highly deformed fragments. Based on those valid fragments, fragment-based color histogram provides a structured and effective description for the object. Finally, the object is tracked using a valid fragment template combining the displacement constraint and similarity of each valid fragment. The object template is updated by fusing feature similarity and valid fragments, which is scale-adaptive and robust to partial occlusion. The experimental results show that the proposed algorithm is accurate and robust in challenging scenarios. © Springer International Publishing Switzerland 2016.

关键词： Bandpass filters

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A Research on Mobile Cloud Computing and Future Trends

EAI Endorsed Transactions on Industrial Networks and Intelli...

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EAI Endorsed Transactions on Industrial Networks and Intelligent Systems 2016年第7期3卷 1-9页

作者： Gu, Fei Niu, Jianwei He, Zhenxue State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing100191 China

With an exploding growth of the mobile applications and emerging of cloud computing, mobile cloud computing (MCC) has become a potential technology for mobile services. MCC is the combination of cloud computing, mobile computing and wireless networks to bring rich computational resources to mobile users, network operators, as well as cloud computing providers. Despite increasing usage of mobile computing, exploiting its full potential is difficult due to its inherent problems such as resource scarcity, frequent disconnections and mobility. MCC can address these problems by executing mobile applications on the resource providers' side. In this paper, we give a definition of mobile cloud computing and provide an overview of state-of-the-art progress, in particular, models of mobile cloud applications. We also highlight research challenges in the area of mobile cloud computing. We conclude that mobile cloud computing can help building more powerful mobile applications. © 2016. Fei Gu et al., licensed to EAI. All Rights Reserved.

关键词： Mobile cloud computing

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Adaptive Fast Mode Decision for HEVC Intra Coding

Adaptive Fast Mode Decision for HEVC Intra Coding

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Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： Rui Tian Yongfei Zhang Rui Fan Gang Wang Beijing Key Laboratory of Digital Media School of Computer Science and Engineering State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China

The latest High Efficiency Video Coding (HEVC) standard offers higher performance than existing video coding standards - up to 50% bit-rate reduction at the equal perceptual quality, but with a significant encoder complexity increase. With regard to intra prediction, a set of 35 intra prediction modes is defined in HEVC to enhance the intra coding performance. However, the high complexity makes it difficult to be applied in real-time applications. To reduce the complexity of intra prediction while maintaining the coding performance, an adaptive fast mode decision algorithm for HEVC intra coding is proposed in this paper, which can efficiently reduce the number of the candidate modes for rate-distortion optimization (RDO) and thus the intra coding time. First, the relation observed between the costs of two candidate modes will be exploited to improve the efficiency of prediction. Second, both the texture consistency of neighborhood and the texture characteristic in current predict unit (PU) will also be considered. Experimental results demonstrate that the proposed algorithm saves 30.12% intra encoding time on average without incurring noticeable performance degradation and outperforms the state-of-the-art fast intra mode decision algorithms by achieving a better RD performance with approximate encoding time saving.

关键词： Encoding Algorithm design and analysis Complexity theory Standards Prediction algorithms

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Detail-Preserving 3D Shape Modeling from Raw Volumetric Dataset via Hessian-Constrained Local Implicit Surfaces Optimization

Detail-Preserving 3D Shape Modeling from Raw Volumetric Data...

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International Conference on Cyberworlds

作者： Shuai Li Dehui Yan Xiangyang Li Aimin Hao Hong Qin State Key Laboratory of Virtual Reality Technology and Systems Beihang University China Beihang University China Department of Computer Science Stony Brook University USA

Massive routinely-acquired raw volumetric datasets are hard to be deeply exploited by cyber worlds related downstream applications due to the challenges in accurate and efficient shape modeling. This paper systematically advocates an interactive 3D shape modeling framework for raw volumetric datasets by iteratively optimizing Hessian-constrained local implicit surfaces. The key idea is to incorporate contour based interactive segmentation into the generalized local implicit surface reconstruction. Our framework allows a user to flexibly define derivative constraints up to the second order via intuitively placing contours on the cross sections of volumetric images and fine-tuning the eigenvector frame of Hessian matrix. It enables detail-preserving local implicit representation while combating certain difficulties due to ambiguous image regions, low-quality irregular data, close sheets, and massive coefficients involved extra computing burden. Moreover, we conduct extensive experiments on some volumetric images with blurry object boundaries, and make comprehensive, quantitative performance evaluation between our method and the state-of-the-art radial basis function based techniques. All the results demonstrate our method's advantages in the accuracy, detail-preserving, efficiency, and versatility of shape modeling.

关键词： Shape Surface reconstruction Three-dimensional displays Solid modeling Image segmentation Image reconstruction Rough surfaces

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OnSeS: A Novel Online Short Text Summarization Based on BM25 and Neural Network

OnSeS: A Novel Online Short Text Summarization Based on BM25...

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2016 IEEE Global Communications Conference (GLOBECOM)

作者： Jianwei Niu Qingjuan Zhao Lei Wang Huan Chen Mohammed Atiquzzaman Fei Peng State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China School of Computer Science University of Oklahoma Norman OK USA Shanghai Research Institute of Aerospace Computer Technology Shanghai China

ISBN: (纸本)9781509013296

The last decade has witnessed a dramatic growth of social networks, such as Twitter, Sina Microblog, etc. Messages/short texts on these platforms are generally of limited length, causing difficulties for machines to understand. Moreover, it is rarely possible for users to read and understand all the content due to the large quantity. So it is imperative to cluster and extract the viewpoints of these short texts. To solve this, the representation of a word is enriched with additional features from external, but it is demanding in terms of computational and time resources. In this paper, we proposed OnSeS, a novel short text summarization method which makes full use of word2vec to represent a word and utilizes neural network model to generate each word of the summary. OnSeS consists of three phrases: 1) clustering short texts using the K-means algorithm; 2) ranking content of each cluster by building a graph-based ranking model using BM25; 3) generating main point of each cluster with the help of neural machine translation model on the top ranked sentence. The experimental results reveal that our proposed fully data-driven approach outperforms state-of-the-art method.

关键词： Clustering algorithms Natural language processing Feature extraction Machine learning Neural networks Solid modeling Semantics

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Interactive Dissection of Digital Organs Based on Metaballs 16

Interactive Dissection of Digital Organs Based on Metaballs

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Proceedings of the 33rd computer Graphics International

作者： Junjun Pan Shizeng Yan Hong Qin State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing China Department of Computer Science Stony Brook University (SUNY Stony Brook) New York USA

ISBN: (纸本)9781450341233

This paper describes an interactive dissection approach based on metaballs for digital organs in virtual surgery. For organ's geometry, we employ a novel hybrid model comprising both inner metaballs and high-resolution surface mesh with texture. Using metaballs, the organ interior is geometrically simplified via a set of overlapping spheres with different radii. For physical representation, we present a hybrid framework to interlink metaballs with moving least squares (MLS) based meshfree method. MLS enables the direct and rapid transition from metaballs to local nodal formulations in physical modeling. For soft tissue dissection, the nature of our MLS-driven meshfree method also facilitates adaptive topology modification and cutting surface reconstruction. As nodal points only exist temporarily in localized regions adjacent to the cutting path, our method could generate accurate cutting surface without sacrificing real-time computational efficiency.

关键词： virtual Surgery Meshfree Metaballs Dissection

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An Efficient Method of Detecting Breathing Frequency While Running

An Efficient Method of Detecting Breathing Frequency While R...

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International Conference on Smart Computing (SMARTCOMP)

作者： Fei Gu Jianwei Niu Sajal K. Das Zhenxue He Beihang University Beijing CN State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China Department of Computer Science Missouri University of Science and Technology Rolla USA

ISBN: (纸本)9781509008995

Breathing plays an important role in the process of running. A stable and harmonic breathing rhythm can postpone runners' fatigue and help to improve their running performances. This paper presents a method that can detect runner's breathing frequency continuously. We utilize Bluetooth headset and smart phone to obtain sensed data, such as striding frequency and breathing frequency. Due to the interference of ambient noise, the detection will be inaccurate. In order to cope with this problem, we calibrate the detection result by leveraging a physiological model, called Locomotor Respiratory Coupling (LRC), which indicates possible ratios between the stride and breathing frequencies. Our method has been validated by extensive experiments and the experimental results indicate that it can accurately detect the breathing frequency for runners.

关键词： Feature extraction Headphones Bluetooth Acceleration Mel frequency cepstral coefficient Training

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A robust approach for long-term hand tracking 12

A robust approach for long-term hand tracking

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12th International Bhurban Conference on Applied Sciences and technology, IBCAST 2015

作者： Abdul Aziz, Muhammad Ali Niu, Jianwei Zhao, Xiaoke State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science Beihang University Beijing China

ISBN: (纸本)9781479963690

Considerable challenges arise in hand tracking due to background clutter, inconsistent lighting, scale changes, occlusions and total object disappearance. In order to cope with these difficulties, we present a robust hand tracker based on enhanced particle filters. To overcome the inherent shortcomings of the particle filter approach, we infuse it with the mean shift (CAMSHIFT) method, thereby reducing the number of the particles and improving their quality. Furthermore, by using detection based on the αHOG (Alpha Histograms of Oriented Gradients) feature proposed in our earlier work [1], our tracker ensures that the hand is re-tracked if it disappears from the image frame and re-enters it. We base our appearance model on RGB color histograms and our newly proposed RLBP (Rotation Invariant Noise Compensated Local Binary Patterns) descriptor, which is an improved version of the LBP (Local Binary Patterns) descriptor. By virtue of our experiments, we show that our proposed tracker shows excellent results in comparison to state-of-the-art trackers on various challenging hand sequences collected by us as well as benchmark object sequences generally used in object tracking. Moreover, our tracker shows strong reacquisition ability, something that the existing hand trackers are not equipped with. © 2015 IEEE.

关键词： Local binary pattern

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A Chinese character component recognition method based on optimal combined strategy

A Chinese character component recognition method based on op...

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IEEE International Conference on computer and Communications, ICCC 2015

作者： Bao, Yongtang Qi, Yue Liu, Min State Key Laboratory of Virtual Reality Technology and Systems School of Computer Science and Engineering Beihang University Beijing China

ISBN: (纸本)9781467381253

Chinese character component recognition plays an important role in Chinese character studying process. In this digital age, using the technology of computer science to analyzing Chinese character component, has a very important significance for the development of traditional culture. In this paper, we propose an optimal combined strategy based method for component recognition. First, we execute preprocessing for all input images. For each image, we process it with image binaryzation and homogenization. Second, we generate the candidate strokes from the results of preprocessing step. Third, we construct the search graph and calculate the possible solution for searching component. Finally, we describe the detailed algorithm for component recognition using optimal combined strategy. Our method can produce accurate Chinese character component recognition results. © 2015 IEEE.

关键词： Chinese character component recognition optimal combined strategy

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