1. A computer-implemented method for applying computer vision techniques to automatically detect and classify the presence or absence of an object within a region of interest, the method comprising executing on a processor the steps of: determining for an auto-correction time period a distribution of object present and object absent labels that are assigned one each to each of a plurality of the video segments of video image scene data acquired from a region of interest, wherein the video segments are each assigned the object present label in response to determining that foreground feature data values meet a background subtraction threshold value indicative of a presence of a foreground object having a specified size, the object absent label in response to determining that the foreground feature data values do not meet the background subtraction threshold value, a motion present label in response to determining that motion feature data values for the frames differ from motion feature data values of previous frames by a motion threshold value that is selected as indicative of a change in visual features consistent with movement of the object within the frame data, and a static label in response to determining that the motion feature data values for the frames do not differ from the motion feature data values of the previous frames by the motion threshold value; in response to determining that the distribution of the object present and the object absent labels does not meet an expected distribution for the auto-correction time period, exchanging the object present and the object absent labels that are assigned to each of the video frames; classifying segments of the input video data comprising consecutive video frames that are each assigned the object absent label and the static label as “no object present” segments; classifying segments of the input video data comprising consecutive video frames that are each assigned the object present label and the motion present label as “object present and in transition” segments; and classifying segments of the input video data comprising consecutive video frames that are each assigned the object present label and the static label as “object present and stopped” segments.