Illumination Invariant Outdoor Perception

Rishi Ramakrishnan Doctor of Philosophy The University of Sydney September 2015 Illumination Invariant Outdoor Perception This thesis proposes the use of a multi-modal sensor approach to achieve illumination invariance in images taken in outdoor environments. The approach is automatic in that it does not require user input for initialisation, and is not reliant on the input of atmospheric radiative transfer models. While it is common to use pixel colour and intensity as features in high level vision algorithms, their performance is severely limited by the uncontrolled lighting and complex geometric structure of outdoor scenes. The appearance of a material is dependent on the incident illumination, which can vary due to spatial and temporal factors. This variability causes identical materials to appear differently depending on their location. Illumination invariant representations of the scene can potentially improve the performance of high level vision algorithms as they allow discrimination between pixels to occur based on the underlying material characteristics. The proposed approach to obtaining illumination invariance utilises fused image and geometric data. An approximation of the physical processes involved in outdoor illumination is used to derive scaling factors for each pixel. This has the effect of relighting the entire scene using a single illuminant that is common in terms of colour and intensity for all pixels. The approach is extended to the multi-image scenario through the use of an overlapping region, meaning that the resultant dataset is both spatially and temporally illumination invariant. This thesis also proposes illumination invariant radiometric normalisation methods, where the aim is to obtain the reflectance spectra of materials in the scene. The ii