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This paper presents a multi-modal affect recognition system that is capable of effectively estimating human affective states through analyzing and fusing a number of non-invasive external cues. The proposed system consists of a probabilistic information fusion model based on the influence diagram and a set of data analysis, feature extraction and affect recognition modules for processing heterogeneous...
Due to the human activities such as artificial beach and reclaiming land from seawaters along Yancheng's coastal area in Jiangsu province in recent years, the problems of coastline straightening and the mudflat prograding have become highlighted. Therefore, it is great significant to master coastline change for shore and mudflats exploitation and utilization, environmental protection and Marine disaster...
Ubiquitous Life Care (u-Life care) nowadays becomes more attractive to computer science researchers due to a demand on a high quality and low cost of care services at anytime and anywhere. Many works exploit sensor networks to monitor patient's health status, movements, and real-time daily life activities to provide care services to them. Context information with real-time daily life activities can...
Motion classification is the first step of gait recognition. The classification of motion is conducted, and behavior validity can be made under specific scenarios. In order to identify people movement in an intelligent security monitoring system, moving body is detected and the boundary is extracted. The paper proposes a complex number notation based on centroid in order to indicate a pedestrian's...
Many video surveillance systems are demanding to monitor moving human behaviors, especially for such environments as jails, warehouses, supermarkets, secret rooms, offices, auditoriums and so on. It has universal significance for image capture of surveillance system to recognize moving human bodies, accordingly, it is an imperative to recognize moving human bodies from other moving objects rather...
Video surveillance is an omnipresent topic when it comes to enhancing security and safety in the intelligent home environments. In this paper, we propose a novel method to detect various posture-based events in a typical elderly monitoring application in a home surveillance scenario. These events include normal daily life activities, abnormal behaviors and unusual events. Due to the fact that falling...
Aimed at the shortcomings of the traditional visual surveillance system, the automatic detection and recognition algorithm of human are studied in intelligent monitoring system. This paper uses the moment eigenvector of head-shoulder's contour as the back-propagation (BP) neural network's input for human identification by building the 2D model of human head-shoulder. Because of adopting the partial...
Resonant frequencies and mode shapes were assessed on 51 human tibiae of healthy persons. In the frequency range of 0 to 1000Hz, three typical resonant frequencies were identified using vibration and modal analysis. These resonant frequencies were corresponding to a rigid body mode (I) at 126 ± 16 Hz in the sagittal plane, a single bending mode (II) at 353 ± 51 Hz and a double bending mode (III) at...
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