Visual object recognition method and apparatus based on manifold distance analysis

Abstract

The invention provides a method for identifying a visual object based on a manifold distance analysis, which comprises the following steps: constructing a manifold of an object to be identified according to data of the visual object to be identified, and constructing the manifold of a known object according to the data of a known visual object; reducing the dimensions of the manifold of the object to be identified and the manifold of the known object to subspaces; extracting the characteristic data in each subspace of the manifold of the object to be identified and the manifold of the known object; calculating the distance between the subspaces so as to obtain the distance between the manifold of the object to be identified and the manifold of the known object; and when the distance between the manifold of the object to be identified and the manifold of the known object meets the identification condition, confirming an object corresponding to the manifold of the known object as the visual object to be identified. The method compares and analyzes the distances between all the subspaces of the manifold of the object to be identified and the manifold of the known object, considers the whole position relations between the manifolds comprehensively, thus the method is not sensitive to noise data and has better identification effect of the visual object.

Description

Technical field [0001] The invention relates to the field of visual object recognition, in particular to a method and device for visual object recognition based on manifold distance analysis. Background technique [0002] Pattern recognition is a process of automatically recognizing shapes, patterns, curves, numbers, character formats and graphics based on a large amount of information and data, based on expert experience and existing knowledge, using computer and mathematical inference methods. As one of the main application areas of pattern recognition, visual object recognition is playing an increasingly important role in aspects such as face recognition and identity recognition. [0003] In the field of visual object recognition, usually the objects of interest are trained from a small number of samples. With the rapid development of video cameras and large-capacity multimedia data storage technologies, the amount of data used for object pattern recognition is also increasing...

AI Technical Summary

Problems solved by technology

This simplifies the calculation of the manifold distance, but because the distance between the closest part of the manifold is often very sensitive to noise data, when two manifolds have closer subspaces due to the influence of noise data, Then the manifold distance calculation analysis is prone to produce wrong results, which leads to misidentification of visual objects

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