Motion Tracking and Occlusion Handling
In instances where the template may not provide a direct match, it may be useful to implement the use of eigenspaces – templates that detail the matching object under a number of different conditions, such as varying perspectives, illuminations, color contrasts, or acceptable matching object “poses”. For example, if the user was looking for a face, the eigenspaces may consist of images (templates) of faces in different positions to the camera, in different lighting conditions, or with different expressions.
It is also possible for the matching image to be obscured, or occluded by an object; in these cases, it is unreasonable to provide a multitude of templates to cover each possible occlusion. For example, the search image may be a playing card, and in some of the search images, the card is obscured by the fingers of someone holding the card, or by another card on top of it, or any object in front of the camera for that matter. In cases where the object is malleable or poseable, motion also becomes a problem, and problems involving both motion and occlusion become ambiguous. In these cases, one possible solution is to divide the template image into multiple sub-images and perform matching on each subdivision.
Read more about this topic: Template Matching
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