Review on Vision-Based Gait Recognition: Representations, Classification Schemes and Datasets

Abstract

Gait has unique advantage at a distance when other biometrics cannot be used since they are at too low resolution or obscured, as commonly observed in visual surveillance systems. This paper provides a survey of the technical advancements in vision-based gait recognition. A wide range of publications are discussed in this survey embracing different perspectives of the research in this area, including gait feature extraction, classification schemes and standard gait databases. There are two major groups of the state-of-the-art techniques in characterizing gait: Model-based and motion-free. The model-based approach obtains a set of body or motion parameters via human body or motion modeling. The model-free approach, on the other hand, derives a description of the motion without assuming any model. Each major category is further organized into several subcategories based on the nature of gait representation. In addition, some widely used classification schemes and benchmark databases for evaluating performance are also discussed.

Person Re-identification based on Robust Features in Open-world

“…Similarities and differences with gait recognition research. Gait recognition [10,20,21], a relatively new research field, has some similarities and differences compared with our research. Different from the existing gait recognition research, our method benefits from the pose estimation model, which can obtain more stable and reliable feature information of pedestrian skeleton key points from images, without the usage of segmentation or spatial subtraction to obtain the pedestrian's unstable body contour features.…”

“…Thus what matters more is how to search for an effective method to extract some stable biological features from images. What we considered is a pedestrian's gait as biological features that is almost fixed in an uninterrupted period of time [10].…”

“…At the meantime, since the pose estimation model [11,12] is robust to image resolution, color, view and other open-world variables, we extract pedestrian skeleton key points as general robust feature information based on pose estimation. Moreover, the continuous frame images can transform the general robust feature information of pedestrians into reliable identity information which has advantages of long distance and longtime effectiveness [10].…”

Gait Recognition based on Inverse Fast Fourier Transform Gaussian and Enhancement Histogram Oriented of Gradient

“…Gait recognition becomes an inspiration as one of the biometric technology applications due to the nature of this study that allows the identification, detection, and recognition of humans through their gait. Gait is defined as the way a person walks [1]- [3]. Gait technology can also be used as human identification systems without requiring interaction with subjects and high-resolution cameras, which makes data collection more accessible.…”

“…GEI is a common gait representation technique, and it is the basis representation techniques proposed [3]. GEI is a method that is still used in the appearance-based study.…”