Papers › Making a long story short: A Multi-Importance fast-forwarding egocentric videos with...
Making a long story short: A Multi-Importance fast-forwarding egocentric videos with the emphasis on relevant objects
Michel Melo Silva, Washington Luis Souza Ramos, Felipe Cadar Chamone, João Pedro Klock Ferreira, Mario Fernando Montenegro Campos, Erickson Rangel Nascimento
The emergence of low-cost high-quality personal wearable cameras combined with the increasing storage capacity of video-sharing websites have evoked a growing interest in first-person videos, since most videos are composed of long-running unedited streams which are usually tedious and unpleasant to watch. State-of-the-art semantic fast-forward methods currently face the challenge of providing an adequate balance between smoothness in visual flow and the emphasis on the relevant parts. In this work, we present the Multi-Importance Fast-Forward (MIFF), a fully automatic methodology to fast-forward egocentric videos facing these challenges. The dilemma of defining what is the semantic information of a video is addressed by a learning process based on the preferences of the user. Results show that the proposed method keeps over 3 times more semantic content than the state-of-the-art fast-forward. Finally, we discuss the need of a particular video stabilization technique for fast-forward egocentric videos.
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