title: Velocity selective filters recursively implemented in the spatiotemporal domain.
abstract: Energy-based methods for motion estimation in image sequences process the input data either in the spatiotemporal or in the frequency domain. In both cases, the algorithms already described in the literature often require a huge number of elementary operations. In this paper, we describe a class of velocity selective filters which yield an accurate detection of the edges moving in the sequence. We first present a filtering scheme based on a convolution operation computed on a finite size neighborhood and describe its properties in the spatiotemporal and frequency domains. Then, we show that filters with similar properties can be implemented recursively, i.e., as convolutions computed on infinite-size neighborhoods. As an example, we finally show the filters' responses in the case of two superimposed translational motions.
authors.affiliation: LEOST Laboratory, INRETS, Villeneuve d'Ascq, France. sebastien.ambellouis@inrets.fr
authors.forename: Sébastien
authors.initials: S
authors.lastname: Ambellouis
authors.forename: François
authors.initials: F
authors.lastname: Cabestaing
authors.forename: Jack-Gérard
authors.initials: JG
authors.lastname: Postaire
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D009068:Movement; D013382:Subtraction Technique; D014741:Video Recording / Q000379:methods*