Region-of-interest tracking system, method and computer program product

Abstract

The invention discloses a region-of-interest tracking method. The region-of-interest tracking method comprises a feature point detecting and tracking module, a linear transformation module, an estimation and update module and an outlier rejection module, wherein the feature point detecting and tracking module detects a local feature point in a region of interest of an image at an initial time, and tracks at least one detected feature point; the linear transformation module calculates a transformation relationship between regions of interest of images of a previous frame and a next frame by utilizing a plurality of tracked corresponding feature points; the estimation and update module estimates and corrects the shift position of the region of interest at a current time; and the outlier rejection module rejects at least one outlier falling outside the region of interest according to a correction result of the estimation and update module over the region of interest. In each embodiment of the invention, the region of interest which may be a moving object or a background or simultaneously comprise the moving object and the background can be stably and smoothly tracked.

Description

technical field [0001] The present invention relates to the field of intelligent monitoring, in particular to a region-of-interest (Region-Of-Interest, ROI for short) tracking system, method and computer program product. Background technique [0002] After the gradual rise of intelligent monitoring systems, the development of some technologies is to use image analysis technology in the back-end system to extract meaningful event information. Fixed cameras have a limited monitoring range and there are dead spots for monitoring. When the event takes place in a large area, fixed cameras cannot obtain a monitoring picture of the overall event. Some technologies are explored by setting up cameras on high-altitude vehicles, such as hot air balloons and unmanned aircraft, to look down at the ground for photography and analyze image monitoring events, and assist the ground monitoring system to monitor a wide range of areas to achieve comprehensiveness without dead ends monitor. ...

AI Technical Summary

Problems solved by technology

This technique uses statistical significance to eliminate outliers, but this optimization process consumes a lot of computing resources

[0008] At present, object tracking technology on flying tools often requires a large number of complex computing resources

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