Computer vision is the scientific discipline concerned with retrieving information from images. An important task in many computer vision applications is discriminating between objects of interest and background objects that are of no interest for the specific application. A well-known approach to address this problem is background subtraction, in which a reference image is subtracted from each input image in order to cancel all objects that are common to the input image and the reference image. This approach works well if the background, as recorded by the imaging system, remains constant, i.e. if the background contains no objects that are susceptible of entering, exiting or moving within the scene (such as e.g. a parked car in a traffic monitoring system) and if the lighting conditions remain the same (which is typically not the case for outdoor image sequences).
If the background may be subject to changes, measures have to be taken to dynamically update the reference image. In article “A practical approach to real-time dynamic background generation based on a temporal median filter” (by B. Shoushtarian et al., Journal of Sciences, Islamic Republic of Iran 14(4), 2003, pp. 351-362), the authors present a real-time dynamic background generation algorithm based upon a temporal median filter with exponentially weighted moving average (EWMA) filtering. The algorithm of this article uses a reference image, which is compared with an incoming image on a pixel-by-pixel basis. If the pixel value of a given pixel of the incoming images remains constant (within a tolerance range) for a certain time, it is assumed that the pixel value is part of the background and that value is copied to the reference image.
A range image is an image, wherein each pixel (image element) contains a range value corresponding to the distance from the imager system to the part of the scene imaged onto the specific pixel. The pixels of a reference range image contain reference range values. As in the case of 2D-imaging, background subtraction in range imaging is simple if the background of the scene is constant. In this case, a constant reference image of the empty scene can be used to remove the background. A problem of this approach is that the background of the scene has to stay constant over the life cycle of the computer vision system; otherwise the output of the system may be wrong. Whereas the assumption of constant background may be justified in laboratory or industrial environment, it is not generally applicable for systems installed in freely accessible areas.