On automatic selection of temporal scales in time-causal scale-space

Tony Lindeberg

Technical report ISRN KTH NA/P--97/09--SE. Department of Numerical Analysis and Computing Science, Royal Institute of Technology, S-100 44 Stockholm, Sweden, Sep 1997.

Also in AFPAC'97: Algebraic Frames for the Perception-Action Cycle (G. Sommer and J. J. Koenderink, eds.), vol. 1315 of Lecture Notes in Computer Science, (Kiel, Germany), pp. 94--113, Springer Verlag, Berlin, Sept. 1997.

Abstract

This paper outlines a general framework for automatic selection in multi-scale representations of temporal and spatio-temporal data, A general principle for automatic scale selection based on local maxima of normalized differential entities is adapted to the temporal domain, and it is shown how the notion of normalized derivatives can be defined for three main types of (continuous and discrete) temporal scale-space representations. Closed-form analysis is carried out for basic model patterns, and shows how the suggested theory applies to motion detection and motion estimation.

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Background: (Spatio-temporal scale-space) (Temporal scale-space) (Scale selection for feature detection) (Monograph on scale-space theory)