A Review of Chinese Academy of Sciences (CASIA) Gait Database As a Human Gait Recognition Dataset

Human Gait as the recognition object is the famous biometrics system recently. Many researchers had focused this subject to consider for a new recognition system. One of the important advantage in this recognition compare to other is it does not require observed subject’s attention and cooperation. There are many human gait datasets created within the last 10 years. Some databases that are widely used are University Of South Florida (USF) Gait Dataset, Chinese Academy of Sciences (CASIA) Gait Dataset, and Southampton University (SOTON) Gait Dataset. This paper will analyze the CASIA Gait Dataset in order to see their characteristics. There are 2 pre-processing subsystems; model based and model free approach. We will use 2D Discrete Wavelet Transform (DWT). We select Haar wavelets to reduce and extract the feature.

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