IEEE Transactions on Image Processing · 2006 · 13 citations · 20 references
Motion DetectionMachine VisionImage AnalysisEngineeringFiltering TechniquePattern RecognitionFilter (Video)Video ProcessingFinite Size NeighborhoodInverse ProblemsConvolution OperationSpatial FilteringVelocity Selective FiltersSignal ProcessingFilter (Signal Processing)Computer VisionImage Sequence AnalysisMotion Analysis
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.
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