Human Motion Analysis Based on Sequential Modeling of Radar Signal and Stereo Image Features

Falls are one of the greatest threats to elderly health in their daily living routines and activities. Therefore, it is very important to detect falls of an elderly in a timely and accurate manner, so that immediate response and proper care can be provided, by sending fall alarms to caregivers. Radar is an effective non-intrusive sensing modality which is well suited for this purpose, which can detect human motions in all types of environments, penetrate walls and fabrics, preserve privacy, and is insensitive to lighting conditions. Micro-Doppler features are utilized in radar signal corresponding to human body motions and gait to detect falls using a narrowband pulse-Doppler radar. Human motions cause time-varying Doppler signatures, which are analyzed using time-frequency representations and matching pursuit decomposition (MPD) for feature extraction and fall detection. The extracted features include MPD features and the principal components of the time-frequency signal representations. To analyze the sequential characteristics of typical falls, the extracted features are used for training and testing hidden Markov models (HMM) in different falling scenarios. Experimental results demonstrate that the proposed algorithm and method achieve fast and accurate fall detections. The risk of falls increases sharply when the elderly or patients try to exit beds. Thus, if a bed exit can be detected at an early stage of this motion, the related injuries can be prevented with a high probability. To detect bed exit for fall prevention, the trajectory of head movements is used for recognize such human motion. A head detector is trained using the histogram of oriented gradient (HOG) features of the head and shoulder areas from recorded bed exit images. A data association algorithm is applied on the head detection results to eliminate head detection false alarms. Then the three dimensional (3D) head trajectories are constructed by matching scale-invariant feature transform (SIFT) keypoints in the detected head areas from both the left and right stereo images. The extracted 3D head trajectories are used for training and testing an HMM based classifier for recognizing bed exit activities. The results of the classifier are presented and discussed in the thesis, which demonstrates the effectiveness of the proposed stereo vision based bed exit detection approach.

Brewing Behind Barbed Wire: An Archaeology of Saké at Amache

After the Japanese attack at Pearl Harbor on December 7, 1941, approximately 120,000 people of Japanese ancestry living on the west coast of the United States were forcibly removed from their home communities. These people were designated as "evacuees" by the U.S. Government and were incarcerated within a network of federal government facilities the largest of which were internment centers operated by the War Relocation Authority that held mostly U.S. citizens. The Granada Relocation Center (Amache) was the smallest of these internment centers. The presence of saké at Amache indicates that Japanese Americans continued important practices of daily life despite restrictions under confinement. This thesis investigates the practices of saké production and consumption at Amache and examines the importance of these practices in Japanese American daily life. In order to understand these practices, this research draws on multiple lines of evidence. This includes investigations of an assemblage of the material culture associated with saké, research into the history and methods of production and consumption, collection of oral histories, review of archival data, and the application of practice theory. These data provide insight into practices that are not well understood by researchers of Japanese American internment due to their illicit nature. This research endeavors to characterize how saké was produced and used at Amache and provides a way to understand how cultural practices maintain aspects of everyday life in ways that may have little to do with intentional resistance.