Deterministic learning theory based gait recognition method irrelevant to visual angle

Abstract

The invention discloses a deterministic learning theory based gait recognition method irrelevant to a visual angle, and belongs to the technical field of pattern recognition. The method comprises the following steps: preprocessing; extracting characteristics; on the basis of extracted gait characteristics, dynamically carrying out neural network modeling and identification to a gait system at different visual angles in a training set; establishing a literal neural network; and constructing a dynamic estimator, and realizing the accurate classification recognition of test modes according to a least error principle by utilizing differences among gait modes on gait system dynamics at different visual angles. The dynamic local accurate modeling and identification of the human body gait system at different visual angles can be realized, meanwhile, gait modes at different visual angles are formed into a uniform training gait mode library, a problem of a traditional method that corresponding training sets need to be independently constructed for gait modes at different visual angles can be overcome, the gait recognition irrelevant to the visual angle is realized, and the invention exhibits higher robustness and practicality.

Description

technical field [0001] The invention belongs to the technical field of pattern recognition, and in particular relates to a gait recognition method based on deterministic learning theory and independent of viewing angle. Background technique [0002] Human gait recognition, as an emerging biometric technology, aims to find and extract the characteristics of individual changes from the same walking behavior, so as to realize automatic identification. The joint angle changes of human walking motion contain rich individual identification information, and human walking motion largely depends on the shape change of body contour over time. This change reflects the unique movement pattern of the individual, which can be effectively identified. Through the analysis of gait, we can get a variety of useful information such as identity, gender, race and so on. In recent years, as the security situation in public places has become more and more serious, a large number of surveillance c...

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Problems solved by technology

[0004] The purpose of the present invention is to overcome the shortcomings of the above-mentioned existing methods that are not robust to changes in viewing angles, and provide a more concise and accurate recognition based on deterministic learning theory for human gaits under different viewing angles, which can adapt to large-scale viewing angle changes. method

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