Autonomous lock-on target tracking with geospatial-aware PTZ cameras

摘要

An autonomous lock-on target tracking system and method with geospatial-aware PTZ cameras includes a camera imaging a terrain space. The camera acquires images, and first and second images are aligned. A frame-differencing operation produces a resultant image including blobs corresponding to elements in the terrain space. One of the blobs is classified as an object and tracked as a target. The target is tracked by determining the distance between a centroid of the target and a center of a field of view of the camera, and instructing the camera to move through the distance. The distance is continually updated as the camera and the target move. Disclosed are also methods for deploying the georeferencing enabled version of such PTZ camera on stationary and mobile land, sea and air platforms.

主权项

1. A video camera surveillance method comprising the steps of:
providing a camera imaging a terrain space in a field of view of the camera, the field of view having a center; acquiring images in a video stream from the camera; forming an image pair of first and second images between two of the images; aligning the first and second images with respect to each other; performing a frame differencing operation on the image pair to form a binary resultant image including blobs corresponding to elements in the terrain space; performing a classification step to classify one of the blobs as an object, the classification step comprising:
determining blob pixels of the one of the blobs in the resultant image;dilating the blob pixels in the resultant image to form dilated blob pixels;determining first image blob pixels and second image blob pixels in the first and second images, respectively, which correspond to the blob pixels in the resultant image;determining first image periphery pixels and second image periphery pixels in the first and second images, respectively, which correspond to the dilated blob pixels in the resultant image less the blob pixels in the resultant image;measuring a first divergence between the first image blob pixels and the first image periphery pixels, in the first image;measuring a second divergence between the second blob pixels and the second image periphery pixels, in the second image; andclassifying the one of the blobs as the object if the second divergence is greater than the first divergence; selecting the object as a target; tracking the target by moving the camera toward the target; and continually repeating the tracking step as the target moves in the terrain space.