System and method for object tracking and timing across multiple camera views

摘要

A system and method for object tracking and timing across multiple camera views includes local and global tracking modules for tracking the location of objects as they traverse particular regions of interest within an area of interest. A local timing module measures the time spent with each object within the area captured by a camera. A global timing module measures the time taken by the tracked object to traverse the entire area of interest or the length of the stay of the object within the area of interest.

主权项

1. A spatio-temporal object tracking system for identifying an object traversing a plurality of video sensor views, including:
a video acquisition system for sensing a plurality of local views of a global area of interest; an object detection module for detecting an object entering one of the local views; a local object tracking module for tracking a motion of the object through the one local view comprising:
assigning an indicator of an at least one invariant representative feature of the object through the global area of interest wherein the at least one invariant representative feature is selected from the group consisting of: license plates, vehicle color, vehicle make, vehicle model, Harris Corners, Scale Invariant Feature Transform (SIFT), Local Binary Patterns (LBP), and Speeded-up Robust Features (SURF);extracting and maintaining each invariant representative feature in a full dataset of interest points per object; a global object tracking module for tracking the object through the plurality of local views and the global area of interest; a local timing module for measuring time data of the object in the one local view; and, a global timing module for measuring time data of the object through the plurality of local views and a length of stay of the object through the global area of interest by synchronization of data across the plurality of video sensor views to achieve timing data normalization across the plurality of video sensor views.