Indexing of Personal Video Captured by a Wearable Imaging System
Digitization of lengthy personal experiences will be made possible by continuous recording using wearable video cameras. It is conceivable that the amount of video content that results will be extraordinarily large. In order to retrieve and browse the desired scenes, a vast amount of video needs to be organized using context information. In this paper, we develop a “Wearable Imaging System” that is capable of constantly capturing data, not only from a wearable video camera, but also from various sensors, such as a GPS, an acceleration sensor and a gyro sensor. The data from these sensors are analyzed using Hidden Markov Model (HMM) to detect various events for efficient video retrieval and browsing. Two kind of browsers are developed which are a chronological viewer and a location based viewer.
KeywordsFeature Vector Hide Markov Model Sensor Data Video Content Acceleration Sensor
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