Disentangled representations for gait recognition
AssigneeBoard of Trustees of Michigan State University
InventorsXiaoming Liu, Ziyuan Zhang
Life of this patent
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Abstract
Gait, the walking pattern of individuals, is one of the important biometrics modalities. Most of the existing gait recognition methods take silhouettes or articulated body models as gait features. These methods suffer from degraded recognition performance when handling confounding variables, such as clothing, carrying and viewing angle. To remedy this issue, this disclosure proposes to explicitly disentangle appearance, canonical and pose features from RGB imagery. A long short-term memory integrates pose features over time as a dynamic gait feature while canonical features are averaged as a static gait feature. Both of them are utilized as classification features.
Claims19
A computer-implemented method for identifying a person, comprising:
- storing a plurality of features sets, such that each feature set corresponds to a different person, where each feature set includes an identifier for a person, canonical features for the person and gait features for the person;
- receiving, by an image processor, a set of images for a given person walking over a period of time;
- extracting canonical features of the given person from the set of images using a first neural network, where the canonical features describe body shape of the given person;
- extracting gait features of the given person from the set of images using the first neural network and a second neural network, where the gait features describe gait of the given person;
- and
- identifying, by the image processor, the given person by comparing the canonical features of the given person and the gait features of the given person to the plurality of feature sets, where the first neural network and the second neural network are implemented by the image processor.
A non-transitory computer readable medium storing a plurality of feature set and a computer program, where each feature set includes an identifier for a person, canonical features for the person and gait features for the person, the computer program, when executed by a processor, perform to:
- receive a set of images for a given person walking over a period of time;
- extract canonical features of the given person from the set of images using a first neural network, where the canonical features describe body shape of the given person;
- extract gait features of the given person from the set of images using the first neural network and a second neural network, where the gait features describe gait of the given person;
- and
- identifying the given person by comparing the canonical features of the given person and the gait features of the given person to the plurality of feature sets.
Dependencies are inferred from the claim text.