A Kalman Filtering Approach to 3-D IR Scene Prediction using Single-Camera Range Video

This paper presents a Kalman filtering approach to predicting 3-D video infrared (IR) scenes as a CMOS multi-coordinate axis sensory-camera mounted on a mobile vehicle moves forward in a controlled environment. Potential applications of this research can be found in indoor/outdoor heat-change based range measurement, synthetic IR scene generation, rescue missions, and autonomous navigation. Experimental results reported herein dictate that linear Kalman filtering based scene prediction accurately estimates future frames in range and intensity sensing. The low least mean square error (LMSE), on the average of 1%, proves the reliability of the approach to IR scene prediction. Currently, the proposed method is devised for piece-wise linear motion of the sensory system as it navigates in hallway or corridor.