presented at the 2008 Video Search Summit
by Dr Marcel Worring, Head of Research for the MediaMill University of Amsterdam.
Marcel discusses the 2 problems that exist, namely, the Semantic Gap, and the Sensory Gap. He then takes you through an incredible video where he demonstrates video visuals of the Semantic Pathfinder Algorithm.
The sensory gap is the gap between the object in the world and the information in a (computational) description derived from a recording of that scene.
For broad image domains in particular, one has to resort to generally valid prin-ciples.
- Is the illumination of the domain white or colored?
- Does it assume fullyvisible objects, or may the scene contain clutter and occluded objects as well?
- Is it a 2D-recording of a 2D-scene or a 2D-recording of a 3D-scene?
The given characteristics of illumination, presence or absence of occlusion, clutter, and diﬀerences in camera viewpoint, determine the demands on the methods of retrieval.
The sensory gap makes the description of objects an ill-posed problem: it yields uncertainty in what is known about the state of the object. The sensory gap is particularly poignant when a precise knowledge of the recording conditions is missing.
The 2D-records of diﬀerent 3D-objects can be identical.Without further knowledge,one has to decide that they might represent the same object.
Also, a 2D-recording of a 3D- scene contains information accidental for that scene and that sensing but one does not know what part of the information is scene related.
The uncertainty due to the sensory gap does not only hold for the viewpoint, but also for occlusion(where essential parts telling two objects apart may be out of sight), clutter, and illumination.
 A.W.M. Smeulders, M. Worring, S. Santini, A. Gupta, and R. Jain, “Content-based image retrieval at the end
of the early years,” IEEE Trans. on PAMI, vol. 22, no. 12, pp. 1349–1380, Dec. 2000.