Object detecting system and method based on multiple classifiers

Abstract

The invention relates to the computer image processing field and discloses an object detection system based on a multi-classifier, which comprises: a classifier training unit used to obtain N classifiers according to the training of a training set, wherein, N is more than one; a classifier selection unit used to select P classifiers from the N classifiers according to the computational amount and the classification performance to fusingly obtain a classifier set, wherein, P is more than one, and is less than or equal to N; a classifier distribution unit used to distribute the P classifiers to a plurality of different computing resources to respectively detect an unknown image to obtain P classifier results; a detection result fusion unit used to fuse the P classifier results to obtain an object detection result. The invention also provides a corresponding method. The invention aims at a plurality of different features in the image to respectively train a plurality of classifiers, and selects the classifiers suitable for distributed operation to be distributed to different computing resources to respectively detect the image, thereby improving the speed of object detection.

Description

technical field [0001] The present invention relates to the field of computer image processing, more specifically, to an object detection system and method based on multi-classifiers. Background technique [0002] Usually, the object detection in the image is mainly realized by object feature representation method and object detection method, in which the object feature representation method extracts features from the image, and then effectively represents the object; while the object detection method uses feature representation to judge the existence of the object . The following is the research status of object feature representation methods and object detection methods. [0003] (a) Object Feature Representation [0004] There are roughly the following types of features: image pixel features, edge features, frequency domain features, local area description features, and histogram features. Table 1 is a comparison of various feature representation methods. [0005] ...

AI Technical Summary

Problems solved by technology

[0011] The technical problem to be solved by the present invention is to provide a multi-classifier-based object detection system and method for the problems of high computational complexity and inability to adapt to real-time processing in the above-mentioned object detection technology

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