Commentary Paper on "Recognizing Shapes in Video Sequences Using Multi-class Boosting"

Author

Salgian, Andrea

Author_Institution

Dept. of Comput. Sci., Coll. of New Jersey, Ewing, NJ, USA

fYear

2008

fDate

1-3 Sept. 2008

Firstpage

75

Lastpage

76

Abstract

This paper describes a learning-based approach to recognizing shapes in video sequences using spatial and temporal features of the shape. The spatial characteristics are encoded in the mean frame, while the temporal characteristics are extracted using the Iwasawa decomposition of the shape sequence. Training is done using logistic regression, namely the LogitBoost algorithm. The method obtains good results on outdoor surveillance datasets.

Keywords

image sequences; learning (artificial intelligence); regression analysis; shape recognition; surveillance; video signal processing; Iwasawa decomposition; LogitBoost algorithm; learning-based approach; logistic regression; multiclass boosting; outdoor surveillance; shape recognition; shape sequence; training; video sequences; Boosting; Fourier transforms; Intelligent vehicles; Lakes; Logistics; Principal component analysis; Shape; Surveillance; Testing; Video sequences;

fLanguage

English

Publisher

ieee

Conference_Titel

Advanced Video and Signal Based Surveillance, 2008. AVSS '08. IEEE Fifth International Conference on

Conference_Location

Santa Fe, NM

Print_ISBN

978-0-7695-3341-4

Electronic_ISBN

978-0-7695-3422-0

Type

conf

DOI

10.1109/AVSS.2008.58

Filename

4730386