Fortinet, Inc.
EXTRACTING REGIONS OF INTEREST FOR OBJECT DETECTION ACCELERATION IN SURVEILLANCE SYSTEMS

Abstract:

Systems and methods for accelerated object detection in a surveillance system are provided. According to an embodiment, video frames captured by a camera are received by a processing resource of a surveillance system. Pixels of each video frame are partitioned into cells each representing a rectangular block of the pixels. The background cells within a particular video frame are estimated by comparing each of the cells of the particular video frame to a corresponding cell of other video frames. A number of ROIs within the particular video frame is detected by: (i) identifying active cells within the particular video frame based on the estimated background cells; and (ii) identifying the number of clusters of cells within the particular video frame by clustering the active cells. Then, object detection is caused to be performed within the number of ROIs by feeding the number of ROIs to a machine learning model.