Using object and trajectory analysis to facilitate indexing and retrieval of video

Authors:
Carlos Lopez;Yi-Ping Phoebe Chen
Affiliations:
School of Engineering and Information Technology, Deakin University Burwood, Vic. 3125, Australia;School of Engineering and Information Technology, Deakin University Burwood, Vic. 3125, Australia
Venue:
Knowledge-Based Systems
Year:
2006

Citing 18
Cited 1

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Abstract

This paper aims to show that by using low level feature extraction, motion and object identifying and tracking methods, features can be extracted and indexed for efficient and effective retrieval for video; such as an awards ceremony video. Video scene/shot analysis and key frame extraction are used as a foundation to identify objects in video and be able to find spatial relationships within the video. The compounding of low level features such as colour, texture and abstract object identification lead into higher level real object identification and tracking and scene detection. The main focus is on using a video style that is different to the heavily used sports and news genres. Using different video styles can open the door to creating methods that could encompass all video types instead of specialized methods for each specific style of video.