Adaptive sub-block screening-based multi-clue visual tracking method

Abstract

The invention belongs to the visual tracking field and relates to an adaptive sub-block screening-based multi-clue visual tracking method. The method comprises the following steps that: (1) saliency detection is performed on a target region, uniform block division is used in combination, so that candidate sub-blocks can be obtained; (2) multi-scale sampling is performed on the candidate sub-blocks, sub-blocks with large frequency-domain response and the corresponding scales of the sub-blocks are determined, and a candidate sub-block set is updated; (3) motion estimation is performed on the sub-blocks in the candidate sub-block set, and the current location of a tracking target is determined through the multi-clue fusion of the sub-blocks; and (4) a Gaussian kernel corresponding to the location of each sub-block is updated through the current location of the target, and sub-blocks which do not satisfy requirements are re-initialized. According to the adaptive sub-block screening-based multi-clue visual tracking method of the invention adopted, the interference of background can be removed, the visual constraints of middle-level features and the priori constraints of high-level languages are fully utilized, so that the locating of the target is more accurate. The adaptive sub-block screening-based multi-clue visual tracking method has the advantages of simple steps and small computation amount, and is suitable for performing visual target tracking under a blocking condition.

Description

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AI Technical Summary

Benefits of technology

This technology improves image processing techniques such as object detection or recognition systems (OCR). It allows us to identify specific objects within an entire scene without overlapping them from other scenes. By dividing up images into smaller blocks based on their visible characteristics, we aimed at finding important parts while also removing irrelevant ones. These methods help achieve higher precision and efficiency than previous algorithms. Additionally, this technique simplifies calculations and enhances performance even when there are partial obscurations between different areas.

Problems solved by technology

This patented technical problem addressed in this patents relates to improving the performance of video cameras during real time monitoring tasks without changing camera settings caused by changes over time. Current techniques involve relying solely upon previous assumptions made about how well they were at detecting objects from different view angles. However, existing approaches have limitations in accurately identifying specific parts of interest within images captured through opaque regions.

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