Showing papers by "Paul A. Viola published in 1996"
TL;DR: In this paper, an information-theoretic approach for finding the registration of volumetric medical images of differing modalities is presented, which is achieved by adjustment of the relative position and orientation until the mutual information between the images is maximized.
2,005 citations
Proceedings Article•
03 Dec 1996TL;DR: This work presents MIMIC, a framework in which it analyzes the global structure of the optimization landscape and uses knowledge of this structure to guide a randomized search through the solution space and, in turn, to refine the structure.
Abstract: In many optimization problems, the structure of solutions reflects complex relationships between the different input parameters. For example, experience may tell us that certain parameters are closely related and should not be explored independently. Similarly, experience may establish that a subset of parameters must take on particular values. Any search of the cost landscape should take advantage of these relationships. We present MIMIC, a framework in which we analyze the global structure of the optimization landscape. A novel and efficient algorithm for the estimation of this structure is derived. We use knowledge of this structure to guide a randomized search through the solution space and, in turn, to refine our estimate ofthe structure. Our technique obtains significant speed gains over other randomized optimization procedures.
524 citations
01 Dec 1996
TL;DR: A new Bayesian framework for visual object recognition which is based on the insight that images of objects can be modeled as a conjunction of local features, and uses a large set of complex features that are learned from experience with model objects.
Abstract: We have developed a new Bayesian framework for visual object recognition which is based on the insight that images of objects can be modeled as a conjunction of local features. This framework can be used to both derive an object recognition algorithm and an algorithm for learning the features themselves. The overall approach, called complex feature recognition or CFR, is unique for several reasons: it is broadly applicable to a wide range of object types, it makes constructing object models easy, it is capable of identifying either the class or the identity of an object, and it is computationally efficient--requiring time proportional to the size of the image. Instead of a single simple feature such as an edge, CFR uses a large set of complex features that are learned from experience with model objects. The response of a single complex feature contains much more class information than does a single edge. This significantly reduces the number of possible correspondences between the model and the image. In addition, CFR takes advantage of a type of image processing called "oriented energy". Oriented energy is used to efficiently pre-process the image to eliminate some of the difficulties associated with changes in lighting and pose.
37 citations
22 Sep 1996
TL;DR: An image guided microscopic surgery system for the navigation of surgical procedures that can overlay renderings of anatomical structures that are otherwise invisible and a new histogram-based mutual information maximization technique was applied.
Abstract: We have developed an image guided microscopic surgery system for the navigation of surgical procedures that can overlay renderings of anatomical structures that are otherwise invisible. A new histogram-based mutual information maximization technique was applied for alignment of the scope view and three-dimensional computer graphics model. This technique doesn't require any pre-processing nor marker setting but is directly applied to the microscope view and the graphics rendering. Therefore, any special set up in image scanning or preoperative preparation is not necessary.
19 citations