Object Tracking with a Novel Visual-Thermal Sensor Fusion Method in Template Matching

Abstract

Recently there has been an increase in the use of thermal-visible conjunction technique in the field of surveillance applications due to complementary advantages of both. An amalgamation of these for tracking requires a reasonable scientific procedure that can efficiently make decisions with sound accuracy and excellent precision. The proposed research presents a unique idea for obtaining a robust track estimate with the thermo-visual fusion in the context of fundamental template matching. This method firstly introduces a haphazard transporting control mechanism for individual modality tracking that avoids unexpected estimates. Then it brings together an efficient computation procedure for providing the weighted output using minimal information from the individual trackers. Experiments performed on publically available datasets mark the usefulness of the proposed idea in the context of accuracy, precision and process time in comparison with the state of art methods.

Deep Learning Based Object Recognition in Real Time Images Using Thermal Imaging System

“…The proposed method is used to recognize the object on it from scene sequence captured by the thermal camera [27]. The basic block diagram of the proposed work is illustrated in figure 1.…”