Title :
Commentary Paper on "Recognizing Shapes in Video Sequences Using Multi-class Boosting"
Author_Institution :
Dept. of Comput. Sci., Coll. of New Jersey, Ewing, NJ, USA
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;
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
DOI :
10.1109/AVSS.2008.58