|Approach: The two methods currently used in modeling the appearance of objects through passive vision are briefly compared here. Geometric approaches determine the shape of an object based on assumed reflectance properties of the object's surface. Image-based approaches use sampling and the reconstruction of the plenoptic function. There is, however, a certain confusion in the literature concerning which method should be categorized as an image approach. Our position to avoid this confusion is simple. An image-based approach is not based on assumed reflectance properties. For example, as soon as a correspondence between images is established, this cannot be referred to as an image-based approach, since establishing a match between images is only possible when the approach is based on a particular reflectance model (usually Lambertian).
Let us briefly recall the advantages and disadvantages of the two approaches. The advantage of image-based approaches is that they are not based on particular reflectance models. Geometric approaches, however, directly allow a change in the lighting conditions under which the object is modeled. Geometric approaches also require less data, thus requiring less photographs of the object and less memory space for the representation of the model.
This research project aims to clearly formulate the problem of modeling the appearance of an object through passive vision. Both geometric and image-based approaches will be investigated. It will be shown that geometric approaches are disadvantaged since their objective of obtaining the true shape of an object is not realistic when using passive vision. An image-based approach will thus be favoured, however, this implies the loss of the advantages of a geometric approach. Thus, it will be shown that the geometric approach does not offer advantages, but instead offers strong hypotheses.