Dual IR spectral video inspection of a concealed live animal

Multi-spectral videos have been used in many different fields, however, most prevalently, in the military and medical application areas. Computer vision experts are especially interested in using satellite-grade infrared (IR) sensors for object detection, recognition and identification (DRI) tasks. There has however, been increased interest in using multi-spectral videos for tasks such as inspection/surveillance, image synthesis, N-D object modeling, collision avoidance and intelligent navigation system development. Implicit in the acquisition and processing of videos (and images) for 3D rigid-body objects are the issues of restoration and registration via the traditional affine transformation. In this paper, we present a dynamic scheme for passive-ID recognition of a 3D deformable object, a live hamster; a recognition-ID generated by the fusion of a long-infrared (LIR), 8-12 mum, and middle-infrared (MIR), 5-8 mum, video cameras. This fusion, based on the nonlinear blind demixing of pixels, was previously applied to perform early passive breast cancer detection. By combining blind pixel demixing of a pair of spectral videos (image sequences) and the adaptive neighborhood histogram modification method, we have generalized local video restoration and registration for a live animal in a concealed environment.