We propose a novel biometrics method based on shadows (shadow biometrics, SB) and introduce a SB-based person identification method for a vision-based surveillance system. Conventional biometric identification based on body movements, as is the case in gait recognition, uses cameras that provide a good view of entire human body. Aerial search and surveillance systems only see the human body from top view with a smaller cross-section and with less details than seen in side views, which is further aggravated by the lower resolution associated with this imagery. Shadows, i.e. body projections due to the Sun, or artificial lights at night, can offer body biometrics information that cannot be directly seen in body top view. In this paper we use SB for person identification, automatically extracting shadows in captured video images, and processing them to extract gait features, further analyzed by spherical harmonics. We demonstrate shadow-based person identification in experiments inside a building using artificial light and outside under the Sun. The introduced method using spherical harmonics outperforms methods based on Fourier transform, gait energy image, and active energy image. Furthermore, we show that the combination of body and shadow areas, as seen from an oblique camera on an upper floor of a building, has better performance than using body only or shadow only information.
All Science Journal Classification (ASJC) codes
- Signal Processing
- Computer Vision and Pattern Recognition
- Artificial Intelligence