MOTION DETECTION USING OPTICAL FLOW

Reduced mobility results in reduced quality of life. The combination of social isolation, limited life space and choice, learned dependence (e.g. requiring someone to push a manual wheelchair), frustration, and limited autonomy likely contributes to symptoms of depression and exacerbation of cognitive impairment and undesirable behaviors. It should also be noted that this chain reaction of symptoms resulting from reduced mobility are also observed in other patient groups beyond older adults (e.g. disabled children, adults with traumatic brain injury, etc.), thus broadening the scope of these problems and requirements from potential solutions. If we can provide these users with some level of independence, irrespective of ability, without placing the person or others at unreasonable risk, then it may be possible to reverse some symptoms of depression and cognitive  impairment and improve quality of life

            The proposed system is a stand-alone image-processing engine . This system is capable of detecting the motions in a video frame. This demo detects a video sequence, from a remote web camera.                         

            Use the Compute optical flow between parameter to specify whether to compute the optical flow between two images or two video frames. If you select Current frame and N-th frame back, the N parameter appears in the dialog box. Enter a scalar value that represents the number of frames between the reference frame and the current frame.

Use the Velocity output parameter to specify the block's output. If you select Magnitude-squared, the block outputs the optical flow matrix where each element is of the form. If you select Horizontal and vertical components in complex form, the block outputs the optical flow matrix where each element is of the form . The horizontal velocity component represents the real part of each value and the vertical velocity component represents the imaginary part of each value.

The smoothness factor, is a positive constant. If the relative motion between the two images or video frames is large, enter a large positive scalar value for the Smoothness factor. If the relative motion is small, enter a small positive scalar value. You must experiment to find the smoothness factor that best suits your application.

The Optical Flow block uses an iterative process to calculate the optical flow between two images or two video frames. Use the Stop iterative solution parameter to control when the iterative process stops. If you want it to stop when the velocity difference is below a certain threshold value, select When velocity difference falls below threshold. Then, use the Velocity difference threshold parameter to specify a threshold value. If you want the iterative process to stop after a certain number of iterations, choose When maximum number of iterations is reached. Then use the Maximum number of iterations parameter to specify the maximum number of iterations you want the block to perform. If you select Whichever comes first, you must enter values for both the Velocity difference threshold and Maximum number of iterations parameters.