A fast algorithm for tracking moving objects based on spatio-temporal video segmentation and cluster ensembles

Author

Monma, Yumi ; Silva, Luciano S. ; Scharcanski, Jacob

Author_Institution

Pos-Grad. em Eng. Eletr., Univ. Fed. do Rio Grande do Sul, Porto Alegre, Brazil

fYear

2015

fDate

11-14 May 2015

Firstpage

29

Lastpage

34

Abstract

This paper presents a fast algorithm to segment moving objects in video sequences, as the first step of a fast object tracking system. It is based on the detection of level lines to detect closed objects contours in a scene. The detected objects are clustered using a combination of mean shift and ensemble clustering. The proposed method produces a temporal video segmentation in a fraction of the processing time required by comparable state-of-the-art particle-based methods.

Keywords

image segmentation; object tracking; spatiotemporal phenomena; video signal processing; ensemble clustering; mean shift combination; moving object tracking; object tracking system; spatio-temporal video segmentation; state-of-the-art particle-based methods; video sequences; Accuracy; Cameras; Clustering algorithms; Databases; Image segmentation; Streaming media; Video sequences; Ensemble clustering; Level lines; Tracking; Video segmentation;

fLanguage

English

Publisher

ieee

Conference_Titel

Instrumentation and Measurement Technology Conference (I2MTC), 2015 IEEE International

Conference_Location

Pisa

Type

conf

DOI

10.1109/I2MTC.2015.7151235

Filename

7151235