Analysis of multi-sensor data, 12 September - 11 December 1968

Analysis of multi-sensor data obtained by Earth Resources Aircraft Progra

ClassCut for Unsupervised Class Segmentation

Abstract. We propose a novel method for unsupervised class segmentation on a set of images. It alternates between segmenting object instances and learning a class model. The method is based on a segmentation energy defined over all images at the same time, which can be optimized efficiently by techniques used before in interactive segmentation. Over iterations, our method progressively learns a class model by integrating observations over all images. In addition to appearance, this model captures the location and shape of the class with respect to an automatically determined coordinate frame common across images. This frame allows us to build stronger shape and location models, similar to those used in object class detection. Our method is inspired by interactive segmentation methods [1], but it is fully automatic and learns models characteristic for the object class rather than specific to one particular object/image. We experimentally demonstrate on the Caltech4, Caltech101, and Weizmann horses datasets that our method (a) transfers class knowledge across images and this improves results compared to segmenting every image independently; (b) outperforms Grabcut [1] for the task of unsupervised segmentation; (c) offers competitive performance compared to the state-of-the-art in unsupervised segmentation and in particular it outperforms the topic model [2].

A low-cost head and eye tracking system for realistic eye movements in virtual avatars

A virtual avatar or autonomous agent is a digital representation of a human being that can be controlled by either a human or an artificially intelligent computer system. Increasingly avatars are becoming realistic virtual human characters that exhibit human behavioral traits, body language and eye and head movements. As the interpretation of eye and head movements represents an important part of nonverbal human communication it is extremely important to accurately reproduce these movements in virtual avatars to avoid falling into the well-known ``uncanny valley''. In this paper we present a cheap hybrid real-time head and eye tracking system based on existing open source software and commonly available hardware. Our evaluation indicates that the system of head and eye tracking is stable and accurate and can allow a human user to robustly puppet a virtual avatar, potentially allowing us to train an A.I. system to learn realistic human head and eye movements

Learning to Teach Argumentation: Research and development in the science classroom

The research reported in this study focuses on an investigation into the teaching of argumentation in secondary science classrooms. Over a one-year period, a group of 12 teachers from schools in the greater London area attended a series of workshops to develop materials and strategies to support the teaching of argumentation in scientific contexts. Data were collected at the beginning and end of the year by audio and video recording lessons where the teachers attempted to implement argumentation. To assess the quality of argumentation, analytical tools derived from Toulmin's argument pattern (TAP) were developed and applied to classroom transcripts. Analysis shows there was development in teachers' use of argumentation across the year. Results indicate that the pattern of use of argumentation is teacher-specific, as is the nature of change. To inform future professional development programmes, transcripts of five teachers, three showing a significant change and two no change, were analysed in more detail to identify features of teachers' oral contributions that facilitated and supported argumentation. The analysis showed that all teachers attempted to encourage a variety of processes involved in argumentation and that the teachers whose lessons included the highest quality of argumentation (TAP analysis) also encouraged higher order processes in their teaching. The analysis of teachers' facilitation of argumentation has helped to guide the development of in-service materials and to identify the barriers to learning in the professional development of less experienced teachers

Non-Hermitian matrix description of the PT symmetric anharmonic oscillators

Schroedinger equation H \psi=E \psi with PT - symmetric differential operator H=H(x) = p^2 + a x^4 + i \beta x^3 +c x^2+i \delta x = H^*(-x) on L_2(-\infty,\infty) is re-arranged as a linear algebraic diagonalization at a>0. The proof of this non-variational construction is given. Our Taylor series form of \psi complements and completes the recent terminating solutions as obtained for certain couplings \delta at the less common negative a.Comment: 18 pages, latex, no figures, thoroughly revised (incl. title), J. Phys. A: Math. Gen., to appea

The AMANDA Neutrino Telescope and the Indirect Search for Dark Matter

With an effective telescope area of order 10^4 m^2, a threshold of ~50 GeV and a pointing accuracy of 2.5 degrees, the AMANDA detector represents the first of a new generation of high energy neutrino telescopes, reaching a scale envisaged over 25 years ago. We describe its performance, focussing on the capability to detect halo dark matter particles via their annihilation into neutrinos.Comment: Latex2.09, 16 pages, uses epsf.sty to place 15 postscript figures. Talk presented at the 3rd International Symposium on Sources and Detection of Dark Matter in the Universe (DM98), Santa Monica, California, Feb. 199

A Shift-Invariant Latent Variable Model for Automatic Music Transcription

In this work, a probabilistic model for multiple-instrument automatic music transcription is proposed. The model extends the shift-invariant probabilistic latent component analysis method, which is used for spectrogram factorization. Proposed extensions support the use of multiple spectral templates per pitch and per instrument source, as well as a time-varying pitch contribution for each source. Thus, this method can effectively be used for multiple-instrument automatic transcription. In addition, the shift-invariant aspect of the method can be exploited for detecting tuning changes and frequency modulations, as well as for visualizing pitch content. For note tracking and smoothing, pitch-wise hidden Markov models are used. For training, pitch templates from eight orchestral instruments were extracted, covering their complete note range. The transcription system was tested on multiple-instrument polyphonic recordings from the RWC database, a Disklavier data set, and the MIREX 2007 multi-F0 data set. Results demonstrate that the proposed method outperforms leading approaches from the transcription literature, using several error metrics

In-situ Analysis of Laminated Composite Materials by X-ray Micro-Computed Tomography and Digital Volume Correlation

The complex mechanical behaviour of composite materials, due to internal heterogeneity and multi-layered composition impose deeper studies. This paper presents an experimental investigation technique to perform volume kinematic measurements in composite materials. The association of X-ray micro-computed tomography acquisitions and Digital Volume Correlation (DVC) technique allows the measurement of displacements and deformations in the whole volume of composite specimen. To elaborate the latter, composite fibres and epoxy resin are associated with metallic particles to create contrast during X-ray acquisition. A specific in situ loading device is presented for three-point bending tests, which enables the visualization of transverse shear effects in composite structures

Protecting against Multidimensional Linear and Truncated Differential Cryptanalysis by Decorrelation

The decorrelation theory provides a different point of view on the security of block cipher primitives. Results on some statistical attacks obtained in this context can support or provide new insight on the security of symmetric cryptographic primitives. In this paper, we study, for the first time, the multidimensional linear attacks as well as the truncated differential attacks in this context. We show that the cipher should be decorrelated of order two to be resistant against some multidimensional linear and truncated differential attacks. Previous results obtained with this theory for linear, differential, differential-linear and boomerang attacks are also resumed and improved in this paper

Non-Markovian quantum trajectories for spectral detection

We present a formulation of non-Markovian quantum trajectories for open systems from a measurement theory perspective. In our treatment there are three distinct ways in which non-Markovian behavior can arise; a mode dependent coupling between bath (reservoir) and system, a dispersive bath, and by spectral detection of the output into the bath. In the first two cases the non-Markovian behavior is intrinsic to the interaction, in the third case the non-Markovian behavior arises from the method of detection. We focus in detail on the trajectories which simulate real-time spectral detection of the light emitted from a localized system. In this case, the non-Markovian behavior arises from the uncertainty in the time of emission of particles that are later detected. The results of computer simulations of the spectral detection of the spontaneous emission from a strongly driven two-level atom are presented