Static hand gesture recognition method fused with BoF model and spectral clustering algorithm

Abstract

The invention relates to an object recognition technology in a static image, in particular to a static hand gesture recognition method fused with a BoF model and a spectral clustering algorithm. The method includes a recognition training method and a recognition application method, a layering BoF model is established to rapidly and accurately catch hand gesture characteristic distribution in a complicated background, characteristic points which belong to the background are filtered out through the spectral clustering algorithm, and efficiencies and accuracy of the recognition are guaranteed. The static hand gesture recognition method fused with the BoF model and the spectral clustering algorithm has the advantages that by means of the layering BoF model, the advantages that traditional BoF models are high in operation efficiency and relatively accurate are maintained, and simultaneously the defect that the traditional BoF models don't contain characteristic point space distribution information is overcome; a filter algorithm (Spectral-HIK) based on spectrum and HIK is provided, by means of the filter algorithm, most of the background characteristic points are filtered out on the basis of maintenance of prospect characteristic points to the greatest extent, and the recognition efficiency and accuracy of the whole algorithm can be effectively improved.

Description

technical field [0001] The invention relates to object recognition technology in static images, in particular to a static gesture recognition method integrating BoF model and spectral clustering algorithm. Background technique [0002] At present, gesture recognition methods can be roughly divided into two categories. The first method is to use auxiliary equipment for gesture recognition, such as Data Gloves, Magnetic Sensors and Inertial Sensors; the second method is computer vision-based gesture recognition algorithms. Compared with the gesture recognition algorithm based on the attached device, this method only uses the camera for data collection, and does not need to attach any other device to the user. However, computer vision-based gesture recognition algorithms face urgent problems. There are two main points: 1) The structural complexity of the human hand itself: a human hand has about 14 joints, which makes the hand extremely flexible. How to distinguish different ...

AI Technical Summary

Problems solved by technology

This method has good recognition results for gesture recognition under known background conditions, but it cannot be applied to gesture recognition under unknown background conditions.

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