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Velocity-adapted spatio-temporal image descriptors for direct recognition of activities

The purpose of this article is to advocate for local velocity adaptation of spatio-temporal receptive fields and to demonstrate advantages of such adaptation when recognising events in time-dependent image sequences. Based on a framework of recursive spatio-temporal scale-space, we first show how a straightforward mechanism for local velocity adaptation can be expressed. We then use such velocity adapted receptive fields for constructing representations of spatio-temporal patterns that are independent of the relative motions between the pattern and the observer. On a test problem of recognizing spatio-temporal activities, we demonstrate how the proposed velocity adaptation scheme, combined with a histogram-based statistical framework, results in a considerable gain in recognition performance, compared to a more traditional approach of using spacetime separable filters without velocity adaptation.