In this paper we propose a novel approach for generating expressive caricatures from an input image. The novelty of this work comes from combining an Active Appearance Model facial feature extraction system with a qua...
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The field of Remote health monitoring now includes technologies such as home and mobile health monitoring, teleretinal imaging, tele-radiology, remote cardiac monitoring, video conferencing and sensors for remote diag...
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ISBN:
(纸本)9781424441488
The field of Remote health monitoring now includes technologies such as home and mobile health monitoring, teleretinal imaging, tele-radiology, remote cardiac monitoring, video conferencing and sensors for remote diagnosis and treatment to patients. In this regard, implantable wireless body sensor networks (IWBSNs) have recently emerged as an important and growing research area. These implantable sensors are required to be reliable, very small, battery-operated, and capable of collecting data, processing it, and transmitting it wirelessly and efficiently. Since these devices are required to run with limited resources (energy, processing, and memory), their utility protocols (collecting, processing, and communication) should be designed carefully, not only to work reliably but, more importantly, to be resource-efficient. The life time of the embedded batteries associated with these sensor nodes varies from a few days to a few weeks as was described in a previous work by the authors. In this paper, we propose a novel technique which allows the implanted sensor nodes to communicate with a base station located outside the body efficiently by consuming the minimum amount of energy. Our proposed protocol allows the battery to last significantly longer even for years with a gain of up to 100's times of power saving. This will improve the quality of patient life, and reduce risk of infection resulting from frequent chirurgical operations needed to replace such implantable batteries. Also, a new time synchronization algorithm is briefly introduced in this work that is especially applicable to our proposed communication protocol.
Three-dimensional models of the spine are very important in diagnosing, assessing, and studying spinal deformities. These models are generally computed using multi-planar radiography, since it minimizes the radiation ...
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To support more effective searches in large-scale weakly-tagged image collections, we have developed a novel algorithm to integrate both the visual similarity contexts between the images and the semantic similarity co...
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ISBN:
(纸本)9781605584805
To support more effective searches in large-scale weakly-tagged image collections, we have developed a novel algorithm to integrate both the visual similarity contexts between the images and the semantic similarity contexts between their tags for topic network generation and word sense disambiguation. First, a topic network is generated to characterize both the semantic similarity contexts and the visual similarity contexts between the image topics more sufficiently. By organizing large numbers of image topics according to their cross-modal inter-topic similarity contexts, our topic network can make the semantics behind the tag space more explicit, so that users can gain deep insights rapidly and formulate their queries more precisely. Second, our word sense disambiguation algorithm can integrate the topic network to exploit both the visual similarity contexts between the images and the semantic similarity contexts between their tags for addressing the issues of polysemes and synonyms more effectively, thus it can significantly improve the precision and recall rates for image retrieval. Our experiments on large-scale Flickr and LabelMe image collections have provided very positive results. Copyright 2009 ACM.
In this paper we show a platform which allows for education and training of a number of essential embedded skills. The Java optimized processor (JOP) is open source and has been used in several educational and trainin...
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We report a series of user studies that evaluate the feasibility and usability of light-weight user authentication with a single tri-axis accelerometer. We base our investigation on uWave, a state-ofthe- art recogniti...
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ISBN:
(纸本)9781605582818
We report a series of user studies that evaluate the feasibility and usability of light-weight user authentication with a single tri-axis accelerometer. We base our investigation on uWave, a state-ofthe- art recognition system for user-created free-space manipulation, or gestures. Our user studies address two types of user authentication: non-critical authentication (or identification) for a user to retrieve privacy-insensitive data;and critical authentication for protecting privacy-sensitive data. For non-critical authentication, our evaluation shows that uWave achieves high recognition accuracy (98%) and its usability is comparable with text IDbased authentication. Our results also highlight the importance of constraints for users to select their gestures. For critical authentication, the evaluation shows uWave achieves state-of-the-art resilience to attacks with 3% false positives and 3% false negatives, or 3% equal error rate. We also show that the equal error rate increases to 10% if the attackers see the users performing their gestures. This shows the limitation of gesture-based authentication and highlights the need for visual concealment.
The current Internet did not define any inherent management constructs and mechanisms;such concepts were added after networking standards and architectures were constructed. This also influenced network management for...
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ISBN:
(纸本)9781424443376
The current Internet did not define any inherent management constructs and mechanisms;such concepts were added after networking standards and architectures were constructed. This also influenced network management for other types of networks. This paper is the first in a series that explores concepts for a new autonomic approach to network management that can be used for current and next generation networks as well as for the Future Internet.
Background generation is very important for accurate object tracking in the video surveillance system. Traditional background generation techniques cause some problems when there have been non-moving objects for a lon...
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The main difficulty in face image modeling is to decompose those semantic factors contributing to the formation of the face images, such as identity, illumination and pose. One promising way is to organize the face im...
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ISBN:
(纸本)9781605586083
The main difficulty in face image modeling is to decompose those semantic factors contributing to the formation of the face images, such as identity, illumination and pose. One promising way is to organize the face images in a higher-order tensor with each mode corresponding to one contributory factor. Then, a technique called Multilinear Subspace Analysis (MSA) is applied to decompose the tensor into the mode-n product of several mode matrices, each of which represents one semantic factor. In practice, however, it is usually difficult to obtain such a complete training tensor since it requires a large amount of face images with all possible combinations of the states of the contributory factors. To solve the problem, this paper proposes a method named M2SA, which can work on the training tensor with massive missing values. Thus M2SA can be used to model face images even when there are only a small number of face images with limited variations which will cause missing values in the training tensor). Experiments on face recognition show that M2SA can work reasonably well with up to 70% missing values in the training tensor. Copyright 2009 ACM.
Biomedical literature is an important source of information in any researcher's investigation of genes, risk factors, diseases and drugs. Often the information searched by public health researchers is distributed ...
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ISBN:
(纸本)9781605588032
Biomedical literature is an important source of information in any researcher's investigation of genes, risk factors, diseases and drugs. Often the information searched by public health researchers is distributed across multiple disparate sources that may include publications from PubMed, genomic, proteomic and pathway databases, gene expression and clinical resources and biomedical ontologies. The unstructured nature of this information makes it difficult to find relevant parts from it manually and comprehensive knowledge is further difficult to synthesize automatically. In this paper we report on LITSEEK (LITerature Search by metadata Enhancement with External Knowledgebases), a system we have developed for the benefit of researchers at the Centers for Disease Control (CDC) to enable them to search the HuGE (Human Genome for Epidemiology) database of PubMed articles, from a pharmacogenomic perspective. Besides analyzing text using TFIDF ranking and indexing of the important terms, the proposed system incorporates an automatic consultation with PharmGKB - a human-curated knowledge base about drugs, related diseases and genes, as well as with the Gene Ontology, a human-curated, well accepted ontology. We highlight the main components of our approach and illustrate how the search is enhanced by incorporating additional concepts in terms of genes/drugs/diseases (called metadata for ease of reference) from PharmGKB. Various measurements are reported with respect to the addition of these metadata terms. Preliminary results in terms of precision based on expert user feedback from CDC are encouraging. Further evaluation of the search procedure by actual researchers is under way. Copyright 2009 ACM.
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