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Recently, the number of elderly people increases in Japan, and the system which supports them is necessary. It is necessary for the system to recognize human action. Then, the system also uses Mining technology. The system confirms the action by using voice recognition. The authors construct this system based on the concept of "Kukanchi". The intelligent space made by basing on the concept...
In this paper, we present a method for extracting footfall locations from three dimensional voxel data created from a pair of silhouettes. With the growth of the elderly population, there is a need for passive monitoring of physical activity to allow older adults to continue living in independent settings. Prior research using anonymized video data has shown good results in passively acquiring information...
In this paper we propose a novel method to detect and record various posture-based and movement-based events of interest in a typical elderly monitoring application in a home surveillance scenario. Posture-based events include standing, sitting, bending/squatting, side lying and lying toward the camera. While movement-based events include running, jumping, active and inactive events. For posture classification,...
In this paper, we propose a real-time system for in-home activity monitoring and functional assessment for elder care. We describe the development of the whole system which could be used to assist the independent living of elders and improve the efficiency of elder care practice. With this system, data is collected, silhouettes extracted, features further analyzed and visualized into graphs from which...
Significant declines in quality of life for elders in assisted living communities are typically triggered by health events. Given the necessary information, such events can often be predicted, and thus, be avoided or reduced in severity. Statistics on activities of daily living and activity level over an extended period of time provide important data for functional assessment and health prediction...
In the paper, we propose a fall detection method based on head tracking within a smart home environment equipped with video cameras. A motion history image and code-book background subtraction are combined to determine whether large movement occurs within the scene. Based on the magnitude of the movement information, particle filters with different state models are used to track the head. The head...
In this work, we study how continuous video monitoring and intelligent video processing can be used in eldercare to assist the independent living of elders and to improve the efficiency of eldercare practice. More specifically, we construct an advanced silhouette extraction and tracking algorithm for indoor environments. An adaptive learning method was developed to estimate the physical location and...
Fall detection system for intelligent home care for elderly people is presented in this paper. The system includes human blob detection by non-parameter background substruction method, feature extraction from two minimum bounding boxes, and fall detection by a cascaded multi-SVM classifier. Besides falling down, other daily activities such as walk, jogging, sitting down, squatting down and immobility...
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