6978911
Information Theoretic Sensor Data Selection for Active Object Recognition and State Estimation
We introduce a formalism for optimal sensor parameter selection for iterative state estimation in static systems. Our optimality criterion is the reduction of uncertainty in the state estimation process, rather than an estimator-specific metric (e.g., minimum mean squared estimate error). The claim is that state estimation becomes more reliable if the uncertainty and ambiguity in the estimation process can be reduced. We use Shannon's information theory to select information-gathering actions that maximize mutual information, thus optimizing the information that the data conveys about the true state of the system. The technique explicitly takes into account the a priori probabilities governing the computation of the mutual information. Thus, a sequential decision process can be formed by treating the a priori probability at a certain time step in the decision process as the a posteriori probability of the previous time step. We demonstrate the benefits of our approach in an object recognition application using an active camera for sequential gaze control and viewpoint selection. We describe experiments with discrete and continuous density representations that suggest the effectiveness of the approach.
16390848
A Fully Projective Formulation to Improve the Accuracy of Lowe's Pose-Estimation Algorithm
Both the original version of David Lowe's influential and classic algorithm for tracking known objects and a reformulation of it implemented by Ishiiet al. rely on (different) approximated imaging models. Removing their simplifying assumptions yields a fully projective solution with significantly improved accuracy and convergence, and arguably better computation-time properties.
14859195
Solving for Set Variables in Higher-Order Theorem Proving
In higher-order logic, we must consider literals with flexible (set variable) heads. Set variables may be instantiated with logical formulas of arbitrary complexity. An alternative to guessing the logical structures of instantiations for set variables is to solve for sets satisfying constraints. Using the Knaster-Tarski Fixed Point Theorem [15], constraints whose solutions require recursive definitions can be solved as fixed points of monotone set functions. In this paper, we consider an approach to higher-order theorem proving which intertwines conventional theorem proving in the form of mating search with generating and solving set constraints.
12227821
DisProt: a database of protein disorder
UNLABELLED
The Database of Protein Disorder (DisProt) is a curated database that provides structure and function information about proteins that lack a fixed three-dimensional (3D) structure under putatively native conditions, either in their entirety or in part. Starting from the central premise that intrinsic disorder is an important structural class of protein and in order to meet the increasing interest thereof, DisProt is aimed at becoming a central repository of disorder-related information. For each disordered protein, the database includes the name of the protein, various aliases, accession codes, amino acid sequence, location of the disordered region(s), and methods used for structural (disorder) characterization. If applicable, most entries also list the biological function(s) of each disordered region, how each region of disorder is used for function, as well as provide links to PubMed abstracts and major protein databases.


AVAILABILITY
www.disprot.org
13531439
Combining Type Theory and Untyped Set Theory
We describe a dependent type theory with proof irrelevance. Within this framework, we give a representation of a form of Mac Lane set theory and discuss automated support for constructing proofs within this set theory. One of the novel aspects of the representation is that one is allowed to use any class (in the set theory) as a type (in the type theory). Such class types allow a natural way of representing partial functions (e.g., the first and second operators on the class of Kuratowski ordered pairs). We also discuss how automated search can be used to construct proofs. In particular, the first-order prover Vampire can be called to solve a challenge problem (the injective Cantor Theorem) which is notoriously difficult for higher-order automated provers.
18741005
Reasoning in Extensional Type Theory with Equality
We describe methods for automated theorem proving in extensional type theory with primitive equality. We discuss a complete, cut-free sequent calculus as well as a compact representation of cut-free (ground) proofs as extensional expansion dags. Automated proof search can be realized using a few operations to manipulate extensional expansion dags with variables. These search operations form a basis for complete search procedures. Procedures based on these ideas are implemented in the higher-order theorem prover Tps.
31238264
The populated web: Browsing, searching and inhabiting the WWW using collaborative virtual environments
This paper presents new approaches for accessing the World Wide Web using multi-user three dimensional spaces, or collaborative virtual environments (CVEs.) The major sections of the paper deal with the aspects of browsing and navigating, searching, populating and displaying information within, and about the WWW. The methods described are illustrated with examples of working applications developed by the authors which together present an image of a possible future for Web access and collaboration based around the Web and its contents.