Bruce Maxwell, Director of Research at Tandent Vision Science, presents the “A Physics-based Approach to Removing Shadows and Shading in Real Time” tutorial at the May 2018 Embedded Vision Summit.
Shadows cast on ground surfaces can create false features and modify the color and appearance of real features, masking important information used by autonomous vehicles, advanced driver assistance systems, pedestrian guides, or autonomous wheelchairs. Maxwell presents a method for generating an illumination-independent image suitable for analysis and classification using a physics-based 2D chromaticity space. To explore its utility, Tandent has implemented a system for removing spatial and spectral illumination variability from roads and pathways that runs at frame rate on embedded processors.
The combination of physics-based pre-processing with a simple classifier to identify road features significantly outperforms a more complex classifier trained to do the same task on standard imagery, while using less computation. Removing illumination variability prior to classification can be a powerful strategy for simplifying computer vision problems to make them practical within the computational and energy budgets of embedded systems.
