Wearable imaging system for summarizing personal experiences
Digitization of lengthy personal experiences would be made possible by constant recording using wearable video cameras. It is conceivable that the resulting amount of video content would be extraordinarily large. In order to retrieve and browse the desired scenes, a vast amount of video would need to be organized with structural information. In this paper, we attempt to develop a "wearable imaging system" that is capable of constantly capturing data, not only from a wearable video camera, but also from various kinds of sensors, such as a GPS, an accelerometer and a gyro sensor. The data from these sensors are appropriately extracted and processed by hidden Markov model (HMM) to achieve efficient video retrieval and browsing.