Multi-Sensor Tracking using a Scalable Condensation Filter

Surveillance and tracking systems typically use a single colour modality for their input. These systems work well in controlled conditions but often fail with low lighting, shadowing, smoke, dust, unstable backgrounds or when the foreground object is of similar colouring to the background. With advances in technology and manufacturing techniques, sensors that allow us to see into the thermal infrared spectrum are becoming more affordable. By using modalities from both the visible and thermal infrared spectra, we are able to obtain more information from a scene and overcome the problems associated with using visible light only for surveillance and tracking. Thermal images are not affected by lighting or shadowing and are not overtly affected by smoke, dust or unstable backgrounds. We propose and evaluate three approaches for fusing visual and thermal images for person tracking. We also propose a modified condensation filter to track and aid in the fusion of the modalities. We compare the proposed fusion schemes with using the visual and thermal domains on their own, and demonstrate that significant improvements can be achieved by using multiple modalities.