Content-based Indoor/Outdoor Video Classification System for a Mobile Platform

Organization of video databases is becoming difficult task as the amount of video content increases. Video classification based on the content of videos can significantly increase the speed of tasks such as browsing and searching for a particular video in a database. In this paper, a content-based videos classification system for the classes indoor and outdoor is presented. The system is intended to be used on a mobile platform with modest resources. The algorithm makes use of the temporal redundancy in videos, which allows using an uncomplicated classification model while still achieving reasonable accuracy. The training and evaluation was done on a video database of 443 videos downloaded from a video sharing service. A total accuracy of 87.36% was achieved.

Authors:

• Mitko Veta
• Tomislav Kartalov
• Zoran Ivanovski

Keywords:

• Indoor/outdoor
• video classification
• imageclassification

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