GONG, COSKER: INTERACTIVE SHADOW REMOVAL AND GROUND TRUTH 1 Interactive Shadow Removal and Ground Truth for Variable Scene Categories

We present an interactive, robust and high quality method for fast shadow removal. To perform detection we use an on-the-fly learning approach guided by two rough user inputs for the pixels of the shadow and the lit area. From this we derive a fusion image that magnifies shadow boundary intensity change due to illumination variation. After de-tection, we perform shadow removal by registering the penumbra to a normalised frame which allows us to efficiently estimate non-uniform shadow illumination changes, re-sulting in accurate and robust removal. We also present the first reliable, validated and multi-scene category ground truth for shadow removal algorithms which overcomes lim-itations in existing data sets – such as inconsistencies between shadow and shadow-free images and limited variations of shadows. Using our data, we perform the most thorough comparison of state of the art shadow removal methods to date. Our algorithm outper-forms the state of the art, and we supply our P-code and evaluation data and scripts to encourage future open comparisons.