A Contents Retrieval Supporting Technique Based on Grasping Pressure

This paper presents a video content retrieval system of operators’ performance areas for camera monitoring and life-logging on a plant operator, fine artist etc. As the system focuses on grasping actions and tool handling operations, it records not only audio-video data, but also grasping pressures by special finger pressure sensors. A sensing module consists of tiny film sensors and a bluetooth wireless data transmitter, in order not to interfere workers’ free actions. Unlike other video retrieval system with voice or image recognition, tag text analysis, the proposed system searches the desired video scene based on grasping pressure data, so that it distinguishes whether the worker operates a tool physically while the worker’s outlook shows holding. As its content browser places only interested video clips on a time line, which the worker handles the tool with a certain force, the user easily knows actual actions among a longer and monotonous raw video sequence. By applying a supervised learning process with known actions in NNmethod, the system extracts the same actions from a video sequence when the user tells the representative action as a search key in the content browser.