Reconciliation of object interaction models

This paper presents Reconciliation+, a tool-supported method which identifies overlaps between models of different object interactions expressed as UML sequence and/or collaboration diagrams, checks whether the overlapping elements of these models satisfy specific consistency rules, and guides developers in handling these inconsistencies. The method also keeps track of the decisions made and the actions taken in the process of managing inconsistencies

Construction of Latent Descriptor Space and Inference Model of Hand-Object Interactions

Appearance-based generic object recognition is a challenging problem because all possible appearances of objects cannot be registered, especially as new objects are produced every day. Function of objects, however, has a comparatively small number of prototypes. Therefore, function-based classification of new objects could be a valuable tool for generic object recognition. Object functions are closely related to hand-object interactions during handling of a functional object; i.e., how the hand approaches the object, which parts of the object and contact the hand, and the shape of the hand during interaction. Hand-object interactions are helpful for modeling object functions. However, it is difficult to assign discrete labels to interactions because an object shape and grasping hand-postures intrinsically have continuous variations. To describe these interactions, we propose the interaction descriptor space which is acquired from unlabeled appearances of human hand-object interactions. By using interaction descriptors, we can numerically describe the relation between an object's appearance and its possible interaction with the hand. The model infers the quantitative state of the interaction from the object image alone. It also identifies the parts of objects designed for hand interactions such as grips and handles. We demonstrate that the proposed method can unsupervisedly generate interaction descriptors that make clusters corresponding to interaction types. And also we demonstrate that the model can infer possible hand-object interactions

Interaction-free measurement with an imperfect absorber

In this paper, we consider interaction-free measurement (IFM) with imperfect interaction. In the IFM proposed by Kwiat et al., we assume that interaction between an absorbing object and a probe photon is imperfect, so that the photon is absorbed with probability 1-\eta (0\leq\eta\leq 1) and it passes by the object without being absorbed with probability \eta when it approaches close to the object. We derive the success probability P that we can find the object without the photon absorbed under the imperfect interaction as a power series in 1/N, and show the following result: Even if the interaction between the object and the photon is imperfect, we can let the success probability P of the IFM get close to unity arbitrarily by making the reflectivity of the beam splitter larger and increasing the number of the beam splitters. Moreover, we obtain an approximating equation of P for large N from the derived power series in 1/N.Comment: 6 pages, 3 eps figures, latex2e; v2: minor corrections; v3: the title is change

Controlling Quantum State Reduction

Every measurement leaves the object in a family of states indexed by the possible outcomes. This family, called the posterior states, is usually a family of the eigenstates of the measured observable, but it can be an arbitrary family of states by controlling the object-apparatus interaction. A potentially realizable object-apparatus interaction measures position in such a way that the posterior states are the translations of an arbitrary wave function. In particular, position can be measured without perturbing the object in a momentum eigenstate.Comment: 9 pages, REVTe

"Interaction-Free" Imaging

Using the complementary wave- and particle-like natures of photons, it is possible to make ``interaction-free'' measurements where the presence of an object can be determined with no photons being absorbed. We investigated several ``interaction-free'' imaging systems, i.e. systems that allow optical imaging of photosensitive objects with less than the classically expected amount of light being absorbed or scattered by the object. With the most promising system, we obtained high-resolution (10 \mu m), one-dimensional profiles of a variety of objects (human hair, glass and metal wires, cloth fibers), by raster scanning each object through the system. We discuss possible applications and the present and future limits for interaction-free imaging.Comment: 10 pages, 6 encapsulated Postscript figure files, accepted for publication in Physical Review