Title

Video Frame Classification Based upon Motion Vectors

DOI

10.6593/FSJ.2015.1401.01

Authors

Ting-Yu Hsu;Wen-Kuei Lin;Che-Yen Wen

Key Words

Surveillance Systems ; Video Frame Classification ; Crime Investigation ; Motion Vectors ; Gaussian Mixture Model

PublicationName

Forensic Science Journal

Volume or Term/Year and Month of Publication

14卷1期(2015 / 12 / 01)

Page #

1 - 32

Content Language

英文

English Abstract

Closed-Circuit Television (CCTV) surveillance systems play an important role in crime scene investigation. Investigators use recorded video data to find suspects and information to solve crime cases. However, there are usually a lot of unwanted or tedious frames (e.g., background without meaning) in surveillance videos. It is an exhausting and time-consuming work for investigators to search entire videos for interested information. The most difficult problem of video data is how to find useful and meaningful frames from them. In this paper, we provide a method of utilizing motion vectors to classify video frames based upon moving information (such as orientation). By the proposed method, investigators can reduce the time of searching objects from surveillance videos, and focus on frames with moving objects.

Topic Category 醫藥衛生 > 基礎醫學