Quasi-periodic spatiotemporal filtering.
This paper presents the online estimation of temporal frequency to simultaneously detect and identify the quasiperiodic motion of an object. We introduce color to increase discriminative power of a reoccurring object and to provide robustness to appearance changes due to illumination changes. Spatial contextual information is incorporated by considering the object motion at different scales. We combined spatiospectral Gaussian filters and a temporal reparameterized Gabor filter to construct the online temporal frequency filter. We demonstrate the online filter to respond faster and decay faster than offline Gabor filters. Further, we show the online filter to be more selective to the tuned frequency than Gabor filters. We contribute to temporal frequency analysis in that we both identify ("what") and detect ("when") the frequency. In color video, we demonstrate the filter to detect and identify the periodicity of natural motion. The velocity of moving gratings is determined in a real world example. We consider periodic and quasiperiodic motion of both stationary and nonstationary objects.
Burghouts
Gertjan J
GJ
Intelligent Systems Lab of Amsterdam, Department of Computer Science, Faculty of Science, University of Amsterdam, The Netherlands. burghout@science.uva.nl
Geusebroek
Jan-Mark
JM
D000465:Algorithms; D001185:Artificial Intelligence; D003116:Color; D003199:Computer Systems; D005374:Filtration / Q000379:methods; 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; D010507:Periodicity; D012815:Signal Processing, Computer-Assisted; D013382:Subtraction Technique; D014741:Video Recording / Q000379:methods*