September 2010: Adrien Angeli presented our paper at BMVC on live feature clustering. This is work in the direction of understanding how appearance and geometry information can be used in a more unified way in visual SLAM than in current systems where place recognition and loop closure detection is done with bag-of-words type approaches which discard geometry when looking up features which represent a place. Can we embed appearance information in the 3D world model in a more integrated way? Here we show a step towards that, be demonstrating that we can cluster the 3D features obtained from visual SLAM into meaningful clusters in real-time, where cluster membership depends both on appearance similarity and geometrical proximity. These clusters may or may not correspond well to objects in the scene, but certainly represent repeatable structure which should have good properties of viewpoint-invariance and we plan to move on to using them for flexible and efficient place recognition, as well as potentially investigating their use for semantic labelling.
Live Feature Clustering in Video Using Appearance and 3D Geometry (PDF format),
Adrien Angeli and Andrew J. Davison, BMVC 2010.
