Person localization and identification are indispensable to provide various personalized services in an intelligent environment. We propose a novel method for person localization and developed a system for identifying...
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ISBN:
(纸本)9783642236778;9783642236785
Person localization and identification are indispensable to provide various personalized services in an intelligent environment. We propose a novel method for person localization and developed a system for identifying up to ten persons in an office room to realize soft authentication. Our system consists of forty-three infrared ceiling sensors with low cost and easy installation. In experiments, the average distance error of person localization was 31.6cm that is an acceptable error for sensors with 1.5m distance to each other. We also confirmed that walking path and speed gives sufficient information for authenticating the user. Through the experiments, we obtained the correct recognition rates of 98%, 95% and 86% for any pair, any three people and all ten people to identify individuals.
As the development of the intellectualization power station's construction, the management for every part of the corporation will change along with it. This research will discuss three parts for the logistics secu...
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ISBN:
(纸本)9783642255373
As the development of the intellectualization power station's construction, the management for every part of the corporation will change along with it. This research will discuss three parts for the logistics security of intellectualization power station which are main contents, management style, management characteristics, and ensure the program of intellectualization power station put into effect successfully from the management of the logistic institution.
The mouth region of human face possesses highly discriminative information regarding the expressions on the face. Facial expression analysis to infer the emotional state of a user becomes very challenging when the use...
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ISBN:
(纸本)9783642245992
The mouth region of human face possesses highly discriminative information regarding the expressions on the face. Facial expression analysis to infer the emotional state of a user becomes very challenging when the user talks, as most of the mouth actions while uttering certain words match with mouth shapes expressing various emotions. We introduce a novel unsupervised method to temporally segment talking faces' from the faces displaying only emotions, and use the knowledge of talking face segments to improve emotion recognition. The proposed method uses integrated gradient histogram of local binary patterns to represent mouth features suitably and identifies temporal segments of talking faces online by estimating the uncertainties of mouth movements over a period of time. The algorithm accurately identifies talking face segments on a real-world database where talking and emotion happens naturally. Also, the emotion recognition system, using talking face cues, showed considerable improvement in recognition accuracy.
This paper proposes a denoising model hybridized using wavelet and bilateral filters with fuzzy soft thresholding. The parameters of the proposed model are optimized with floating point genetic algorithm (FPGA). The m...
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ISBN:
(纸本)9783642240546;9783642240553
This paper proposes a denoising model hybridized using wavelet and bilateral filters with fuzzy soft thresholding. The parameters of the proposed model are optimized with floating point genetic algorithm (FPGA). The model optimized with one image is used as a general denoising model for other images like Lena, Fetus, Ultrasound, Xray, Baboon, and Zelda. The performance of the proposed model is evaluated in denoising images injected with noises in different degrees;moderate, high and very high, and the results obtained are compared with those obtained with similar hybrid model with wavelet soft thresholding. Results demonstrate that the performance of the proposed model in terms of PSNR and IQI in denoising most of the images is far better than those with similar model with wavelet soft thresholding. It has also been observed that the hybrid model with wavelet soft thresholding fails to denoise images with very high degree of noises while the proposed model can still be capable of denoising.
Emotion recognition from natural speech is a very challenging problem. The audio sub-challenge represents an initial step towards building an efficient audio-visual based emotion recognition system that can detect emo...
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ISBN:
(纸本)9783642245701
Emotion recognition from natural speech is a very challenging problem. The audio sub-challenge represents an initial step towards building an efficient audio-visual based emotion recognition system that can detect emotions for real life applications (i.e. human-machine interaction and/or communication). The SEMAINE database, which consists of emotionally colored conversations, is used as the benchmark database. This paper presents our emotion recognition system from speech information in terms of positive/negative valence, and high and low arousal, expectancy and power. We introduce a new set of features including Co-Occurrence matrix based features as well as frequency domain energy distribution based features. Comparisons between well-known prosodic and spectral features and the new features are presented. Classification using the proposed features has shown promising results compared to the classical features on both the development and test data sets.
The wide application of General Purpose Graphic Processing Units (GPGPUs) results in large manual efforts on porting and optimizing algorithms on them. However, most existing automatic ways of generating GPGPU code fa...
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In this paper, we are interested in a segmentation method integrating a priori knowledge of shape, that of active deformable shapes known as ASM (Active Shape Model). We have proposed to add to this method one extra c...
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Cortical folding patterns are believed to be good predictors of brain cytoarchitecture and function. For instance, neuroscientists frequently apply their domain knowledge to identify brain Regions of Interests (ROIs) ...
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ISBN:
(纸本)9783642236280
Cortical folding patterns are believed to be good predictors of brain cytoarchitecture and function. For instance, neuroscientists frequently apply their domain knowledge to identify brain Regions of Interests (ROIs) based on cortical folding patterns. However, quantitative mapping of cortical folding pattern and brain function has not been established yet in the literature. This paper presents our initial effort in quantification of the regularity and variability of cortical folding pattern features for working memory ROIs identified by task-based fMRI, which is widely accepted as a standard approach to localize functionally-specialized brain regions. Specifically, we used a set of shape attributes for each ROI base on multiple resolution decomposition of cortical surfaces, and described the meso-scale folding pattern via a polynomial-based approach. We also applied brain atlas label distribution as a global-scale description of ROT folding pattern. Our studies suggest that there is deep-rooted regularity of cortical folding patterns for certain working memory ROIs across subjects, and folding pattern attributes could be useful for the characterization, recognition and prediction of ROIs, if extracted and applied in a proper way.
FP-growth is the most famous algorithm for discovering frequent patterns. As the database size growths or the minimum support decreases, however, both of the memory requirement and execution time increase greatly. Man...
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Stemmer is important especially for information and document retrieval. It can also help to reduce the size of the dictionary. Normally Malay stemmers need to have a root word dictionary to increase the stemmer's ...
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