Velocity adaptation of space-time interest points
Ivan Laptev and Tony Lindeberg
In Proc. ICPR 2004, Cambridge, UK.
Abstract
The notion of local features in space-time has recently been
proposed to capture and describe local events in video.
When computing space-time descriptors, however, the result may
strongly depend on the relative motion between the
object and the camera.
To compensate for this variation, we present a method
that automatically adapts the features to the local velocity
of the image pattern and, hence, results in a video
representation that is stable with respect to different
amounts of camera motion.
Experimentally we show that the use of velocity adaptation
substantially increases the repeatability of interest points
as well as the stability of their associated descriptors.
Moreover, for an application to human action recognition we
demonstrate how velocity-adapted features enable recognition of
human actions in situations with unknown camera motion and
complex, non-stationary backgrounds.
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Related projects:
Recognition of human actions
Related publications:
(Local descriptors for spatio-temporal recognition)
(Recognizing Human Actions: a Local SVM Approach)
(Space-time interest points)
(Interest point detection and scale selection in space-time)
(Velocity-adaptation of spatio-temporal receptive fields for
direct recognition of activities: An experimental study)
(Monograph on scale-space theory)
Ivan Laptev