Vision-Based Approach to Senior Healthcare: Depth-Based Activity Recognition with Convolutional Neural Networks
نویسندگان
چکیده
Recent progress in developing cost-effective sensors and machine learning techniques have enabled new AI-assisted solutions for human behavior understanding. In this work, we aim to investigate the use of depth sensors for the detection of daily activities, lifestyle patterns, and vital signs, as well as the development of intelligent mechanisms for accurate situational assessment and rapid response. Using the dataset we collected at On Lok, a senior home in San Francisco, we propose to build and demonstrate an integrated solution for remote monitoring, assessment, and support of seniors living independently at home using computer vision techniques such as 3D convolutional neural networks and LSTMs. We also introduce a new database and annotation framework consisting of labeled activities for senior citizens.
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