Yuichiro Takeuchi
ABSTRACT
In this paper, we propose a video summarization system which takes into account users' individual preferences by using their personal photo libraries. Nowadays it is common, especially among people of younger generations, to store thousands of photos inside their PCs and manage them using software such as iPhoto and Picasa. These personal photo libraries contain rich information about the user's tastes, personalities, and lifestyles. Since still photos are in many aspects similar to video as a medium, we assume that these personal photo libraries can be used to estimate users' preferences on video summarization.Our system first divides a movie into short segments, and uses image classification techniques to judge whether each segment is meaningful to the user or not. If many photos with contents similar to the segment can be found in the user's photo library, the segment is judged as being "important" to the user. Conventional image classification techniques use public or commercial photo databases as training data, while our system uses personal photo libraries. This difference leads to the need of several modifications in the classification process.We have implemented a prototype version of our system, and have validated the effectiveness of our approach through evaluating both the accuracy of our image classification algorithm, and users' subjective satisfaction levels of the summarization results.
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Index Terms
- Video summarization using personal photo libraries
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