Improved Frame Differencing based Moving Object Detection using Feet-Step Sound

摘要

Moving objects have been detected using various object detection techniques. Two categories for moving object detection techniques are frame differencing based and background subtraction based. These techniques are limited by camera scene complexity, light conditions, video type etc. Frame differencing based techniques process videos faster compared to background subtraction based techniques. Frame differencing based techniques detects only the boundary of the moving object and may fail for slow moving objects. These techniques for moving object detection can be improved by using sound data as most video recording cameras are equipped with a microphone. Sounds from human footsteps can be recorded with video and used with frame differencing techniques to improve moving object detection results. Camera microphones also record background noise with other background sound. This noisy data has been filtered out using the Fourier transform. When peak locations for each footstep sound are determined, and a Full Width at Half Maxima is computed for each peak, the.number of frames within this width are counted, these frames are verify the presence of a moving object.