Fast video object tracking using affine invariant normalization

Tzouveli, P; Avrithis, Y; Kollias, S

dc.contributor.author	Tzouveli, P	en
dc.contributor.author	Avrithis, Y	en
dc.contributor.author	Kollias, S	en
dc.date.accessioned	2014-03-01T01:24:24Z
dc.date.available	2014-03-01T01:24:24Z
dc.date.issued	2006	en
dc.identifier.issn	15715736	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/17246
dc.subject	Affine Transformation	en
dc.subject	Moving Object	en
dc.subject	Computer Vision and Image Processing	en
dc.subject	Video Object	en
dc.title	Fast video object tracking using affine invariant normalization	en
heal.type	journalArticle	en
heal.identifier.primary	10.1007/0-387-34224-9_64	en
heal.identifier.secondary	http://dx.doi.org/10.1007/0-387-34224-9_64	en
heal.publicationDate	2006	en
heal.abstract	One of the most common problems in computer vision and image processing applications is the localization of object boundaries in a video frame and its tracking in the next frames. In this paper, a fully automatic method for fast tracking of video objects in a video sequence using affine invariant normalization is proposed. Initially, the detection of a video object is achieved using a GVF snake. Next, a vector of the affine parameters of each contour of the extracted video object in two successive frames is computed using affine-invariant normalization. Under the hypothesis that these contours are similar, the affine transformation between the two contours is computed in a very fast way. Using this transformation to predict the position of the contour in the next frame allows initialization of the GVF snake very close to the real position. Applying this technique to the following frames, a very fast tracking technique is achieved. Moreover, this technique can be applied on sequences with very fast moving objects where traditional trackers usually fail. Results on synthetic sequences are presented which illustrate the theoretical developments. © 2006 International Federation for Information Processing.	en
heal.journalName	IFIP International Federation for Information Processing	en
dc.identifier.doi	10.1007/0-387-34224-9_64	en
dc.identifier.volume	204	en
dc.identifier.spage	549	en
dc.identifier.epage	556	en