Research On Practical Gait Database Construction And Gait Feature Extraction And Expression

Gait recognition is one of the ideal technologies for unobtrusive security surveillance and human identification at a distance. The quantity of the extracted gait features is important to recognition. And it has not been figured out how to construct the gait database for a practical gait recognition system. Focusing on these two prominent questions between the gait recognition technology and the practical system, this dissertation mainly includes the following issues:①A method of constructing a practicality gait Database is presented. The Database constructed procedure, data structure and the obtained method of the gait are discussed in detail. Thanks for young students’passional participation, A gait database with multifarious gait information of110individuals is established. It is used for all studies in this paper.②A gait recognition method based on the database technology is proposed. The method of constructing the gait database combining with the relational database technology is presented. And the method that used the high efficien-cy of query in the relational database to reduce the individual set for the gait recognition algorithm to identify is presented. The particular design of the gait feature database, including the construction method and the data structure, the gait sampling method and the determine of the query condition about the in-dividual height range are depicted. Experimental results demonstrate that this practical gait database could availably support the gait recognition algorithm to identify the individuals more quickly and more exactly.③A gait feature expression with the semi-periodicity based on the Spatio-Temporal Energy image is described, in which the semi-periodicity and the Spatio-Temporal Energy image are defined formally. And it has been proved insensitive to noise by the statistical analysis. Experiments combining this expression with other gait feature extraction method show that this gait expression simplified the pretreatment of the gait recognition greatly, depressed the storage of the gait features, and reduced the dependence of the gait feature extraction on the step speed and the video sampling frequency, while the recognition performance possessed some practical merit.④Making use of the advantage of wavelets analysis which could express signal local feature well, and combined the mutual information merit, a bionic gait recognition based the wavelets analysis and the mutual information is proposed. The similar subimage and three detail subimages containing local orientation characters from wavelets transformation are all utilized into the combined gait feature. When the maximum mutual information gained, the optimal coefficients for the extracted combined gait feature are determined. these coefficients give prominence to particular walking habit differences of a individual, which make the combined gait feature focus on the key information discriminative for human identification and the procedure of gait recognition by computer system is more closed to the intelligent human vision.