Several interesting monitoring applications concern people entering a prescribed area, where they deposit an object in their possession, or collect an object deposited earlier. One example arises in the use of bicycle racks. We propose a novel method for associating each person who deposits an object with the person who later collects it. Our main contribution is to deal with ambiguity in the visual data through the use of global constraints on what is possible. The method is evaluated on a set of practical experiments in a bicycle rack, and applied to online theft detection by comparing the colour profile of associated individuals.
|Title of host publication||British Machine Vision Conference (BMVC)|
|Publication status||Published - 2007|