11. A computer implemented method of detecting one or more vehicles in a video frame acquired from a fixed parking occupancy video camera including a field of view associated with a vehicle parking region, the method comprising: a) capturing a video frame from the fixed parking occupancy video, the video frame including a ROI (Region of Interest) oriented by an orientation angle relative to an orientation of an image plane associated with the captured video frame, the ROI including one or more parking spaces of the vehicle parking region; b) performing a sliding window-based search for one or more vehicles within the ROI, the sliding window-based search extracting one or more features associated with each of a plurality of candidate search windows representing a set of windows from which object bounding boxes are selected, wherein each selected object bounding box is associated with a vehicle, and wherein the vehicle is not associated with any of the other object bounding boxes; c1) accessing a classifier to score each candidate search window with a classification score calculated by the classifier indicating a probability of candidate search window includes a vehicle relative to a plurality of training images used to train the classifier; c2) degrading the classification score of one or more classified overlapping search windows including a common vehicle, the classification score degraded by an amount that is a function of an overlap area of the overlapping search windows and a relative size of each of the overlapping windows; and d) performing a NMS (Non-Maximal Suppression) process to suppress any overlapping classified candidate search window with a classification score below a predetermined threshold, wherein classified candidate search windows which are not suppressed are considered to be object bounding boxes representative of the one or more vehicles detected in the video frame.
17. The computer implemented method of detecting one or more vehicles in a video frame according to claim 11 , wherein the classifier is one of a neural network classifier, a K-nearest neighbor classifier, a linear SVM (Support Vector Machine) classifier and a non-linear SVM classifier.