With the rapid development of computers and the increasing, mass use of high-tech mobile devices, vision-based face recognition has advanced significantly. However, it is hard to conclude that the performance of computers surpasses that of humans, as humans have generally exhibited better performance in challenging situations involving occlusion or variations. Motivated by the recognition method of humans who utilize both holistic and local features, we present a computationally efficient hybrid face recognition method that employs dual-stage holistic and local feature-based recognition algorithms. In the first coarse recognition stage, the proposed algorithm utilizes Principal Component Analysis (PCA) to identify a test image. The recognition ends at this stage if the confidence level of the result turns out to be reliable. Otherwise, the algorithm uses this result for filtering out top candidate images with a high degree of similarity, and passes them to the next fine recognition stage where Gabor filters are employed. As is well known, recognizing a face image with Gabor filters is a computationally heavy task. The contribution of our work is in proposing a flexible dual-stage algorithm that enables fast, hybrid face recognition. Experimental tests were performed with the Extended Yale Face Database B to verify the effectiveness and validity of the research, and we obtained better recognition results under illumination variations not only in terms of computation time but also in terms of the recognition rate in comparison to PCA- and Gabor wavelet-based recognition algorithms.
Falls are a major problem for the elderly people leading to injury, disability, and even death. In this article, we propose a fall detection system that uses the acceleration sensor of a smartphone to detect a senior citizen falling in real time and to use the communication capabilities of the smartphone to notify the administrator of such an event. The proposed system conducts real-time location tracking using Google's Map and 3D information to cope with a critical situation and to make an urgent intervention in an emergency. Since Google's 3D mapping service can provide information on the surrounding buildings and their shapes with more precision than a 2D service or text-based service, it is possible to ensure a prompt response for senior citizens when such location information is available. To verify the validity and efficiency of this article, we measured the change in acceleration sensor value by classifying the subjects by age group and gender. As a result, we found that the signal vector magnitude value of the acceleration sensor value variation showed a great difference in daily life such as walking, running, sitting, and falling.
Nowadays Web users have clearly expressed their wishes to receive personalized services directly. Personalization is the way to tailor services directly to the immediate requirements of the user. However, the current Web Services System does not provide any features supporting this such as consideration of personalization of services and intelligent matchmaking. In this research a flexible, personalized Rule-based Web Services System to address these problems and to enable efficient search, discovery and construction across general Web documents and Semantic Web documents in a Web Services System is proposed. This system utilizes matchmaking among service requesters', service providers' and users' preferences using a Rule-based Search Method, and subsequently ranks search results. A prototype of efficient Web Services search and construction for the suggested system is developed based on the current work.
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