Wavelet MACH filter for omnidirectional human action recognotion - Ang, Tyzz Kae (2012)
Action recognition is important in the field of intelligent security and surveillance. However, most surveillance cameras can only capture in one direction with limited viewing angle. This research proposes an edge enhancement template based method of omnidirectional action recognition that is able to detect specific actions at a 360 degree of panoramic view. The unwarping of an omnidirectional image into a panoramic image further enables the use of existing image processing algorithm. Besides that, it also allows user to observe familiar panoramic image instead of an unfamiliar omnidirectional image. A MACH filter captures intra-class variability by synthesizing a single action MACH filter for a given action class. The proposed method, based on the wavelet MACH filter, provides additional flexibility of an adaptive choice of wavelet scale factors and, in doing so, enables the selection of the size and orientation of the smoothing function in edge enhancement to optimize the performance of the MACH filter.