A novel method to represent repetitive and overwriting activities in motion history images

Motion History Images(MHI) are extensively being used to represent the history of temporal changes involved in the execution of an activity. Here the intensity of the pixels of a scalar valued image are varied, depending upon the motion history. MHI suffers from a very prominent drawback that when self-occluding or over-writing activities are encountered it fails to generate a vivid description of the course of that activity. This happens because when repetitive activities are performed, the current action overwrites or deletes the information of the previous action. In this paper, we have designed a methodology which has overcome this problem of conventional MHI. In our mechanism, we have used red, green and blue channels to represent human movement. Initially the pixel values of all the three channels are null. When any motion is detected at a particular pixel for the first time, then it is represented using MHI_R. However, if a repetitive action is performed, then it is represented using MHI_G and if overwriting action is thereafter continued for the second time, then MHI_B is utilized. In this approach, the pixel intensities are varied in accordance with the basic MHI. Thus, using our methodology which uses multiple channels, MHI is not only capable of detecting the history of motion but is also made capable of representing overlapping repetitive actions.