Semi-automatic image annotation sample generating method based on target tracking

Abstract

The invention discloses a semi-automatic image annotation sample generating method based on target tracking. The method comprises processes of target tracking and semi-automatic annotation. A serial of samples are generated through a target tracking mechanism, a template learning mechanism is designed for tracking and detecting target areas, detection on videos or images is performed by means of learned templates, manual annotation is utilized to help to perform determination, and therefore, annotation samples are generated. The semi-automatic image annotation sample generating method based on the target tracking has the advantages of being capable of obtaining a large amount of image annotation samples by means of less labor consumption.

Description

technical field

[0001] The invention relates to a method for generating semi-automatic image annotation samples based on target tracking, and belongs to the technical field of image processing. Background technique

[0002] The goal of image annotation is to establish the correspondence between image regions and annotated keywords. Image annotation can solve the "semantic gap" problem in image retrieval to a certain extent by establishing the mapping relationship between low-level visual features and high-level semantics. Image annotation can be divided into two categories: manual annotation and automatic annotation. Manual image annotation is the most direct and effective way, but it is also a very time-consuming and labor-intensive task. With the development of the Internet and digital image technology, image data has grown massively. The traditional manual labeling method can only label the object area in one image at a time, and manual labeling is more and more time-co...

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