One promising extension of gait recognition is to use inputs from multiple or moving cameras. To improve performance, gait recognition can be combined with other biometric features such as face images. Because of its suitability for security camera applications, silhouette-based gait recognition is occasionally used for forensics. In particular, silhouette-based gait features, which use silhouettes of people walking, achieve state-of-the-art performance when using distant views (i.e., low-resolution images) as the input, compared with model-based approaches that fit human shape models.
Gait recognition, i.e., the identification of individuals from their walking styles, is another technique that offers promising solutions for applications that use security cameras, which capture pedestrians from distant positions.
However, face recognition is notably difficult when the quality of facial features is insufficient, for example, due to the person looking down or to low-resolution input images. Face recognition is a typical instance that achieves great success due to its practical recognition performance.
A particularly active area of study is the identification of individuals for security purposes using vision sensors placed in distant positions (e.g., security cameras). Individual identification is a core problem in the computer vision and biometrics fields.
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