Using segmented objects in ostensive video shot retrieval

This paper presents a system for video shot retrieval in which shots are retrieved based on matching video objects using a combination of colour, shape and texture. Rather than matching on individual objects, our system supports sets of query objects which in total reflect the user’s object-based information need. Our work also adapts to a shifting user information need by initiating the partitioning of a user’s search into two or more distinct search threads, which can be followed by the user in sequence. This is an automatic process which maps neatly to the ostensive model for information retrieval in that it allows a user to place a virtual checkpoint on their search, explore one thread or aspect of their information need and then return to that checkpoint to then explore an alternative thread. Our system is fully functional and operational and in this paper we illustrate several design decisions we have made in building it

A comparative evaluation of interest point detectors and local descriptors for visual SLAM

Abstract In this paper we compare the behavior of different interest points detectors and descriptors under the conditions needed to be used as landmarks in vision-based simultaneous localization and mapping (SLAM). We evaluate the repeatability of the detectors, as well as the invariance and distinctiveness of the descriptors, under different perceptual conditions using sequences of images representing planar objects as well as 3D scenes. We believe that this information will be useful when selecting an appropriat

Application of the Gaussian mixture model in pulsar astronomy -- pulsar classification and candidates ranking for {\it Fermi} 2FGL catalog

Machine learning, algorithms to extract empirical knowledge from data, can be used to classify data, which is one of the most common tasks in observational astronomy. In this paper, we focus on Bayesian data classification algorithms using the Gaussian mixture model and show two applications in pulsar astronomy. After reviewing the Gaussian mixture model and the related Expectation-Maximization algorithm, we present a data classification method using the Neyman-Pearson test. To demonstrate the method, we apply the algorithm to two classification problems. Firstly, it is applied to the well known period-period derivative diagram, where we find that the pulsar distribution can be modeled with six Gaussian clusters, with two clusters for millisecond pulsars (recycled pulsars) and the rest for normal pulsars. From this distribution, we derive an empirical definition for millisecond pulsars as $\frac{\dot{P}}{10^{-17}} \leq3.23(\frac{P}{100 \textrm{ms}})^{-2.34}$. The two millisecond pulsar clusters may have different evolutionary origins, since the companion stars to these pulsars in the two clusters show different chemical composition. Four clusters are found for normal pulsars. Possible implications for these clusters are also discussed. Our second example is to calculate the likelihood of unidentified \textit{Fermi} point sources being pulsars and rank them accordingly. In the ranked point source list, the top 5% sources contain 50% known pulsars, the top 50% contain 99% known pulsars, and no known active galaxy (the other major population) appears in the top 6%. Such a ranked list can be used to help the future follow-up observations for finding pulsars in unidentified \textit{Fermi} point sources.Comment: 9 pages, 4 figures, accepted by MNRA

A hybrid nonlinear-discriminant analysis feature projection technique

Feature set dimensionality reduction via Discriminant Analysis (DA) is one of the most sought after approaches in many applications. In this paper, a novel nonlinear DA technique is presented based on a hybrid of Artificial Neural Networks (ANN) and the Uncorrelated Linear Discriminant Analysis (ULDA). Although dimensionality reduction via ULDA can present a set of statistically uncorrelated features, but similar to the existing DA's it assumes that the original data set is linearly separable, which is not the case with most real world problems. In order to overcome this problem, a one layer feed-forward ANN trained with a Differential Evolution (DE) optimization technique is combined with ULDA to implement a nonlinear feature projection technique. This combination acts as nonlinear discriminant analysis. The proposed approach is validated on a Brain Computer Interface (BCI) problem and compared with other techniques. © 2008 Springer Berlin Heidelberg

Plasma Electronics

Contains reports on twelve research projectsU. S. NavyU.S. Navy (Office of Naval Research) under Contract Nonr-1841(78)U. S. Air Force under Air Force Contract AF 19(604)-7400U. S. ArmyNational Science Foundation (Grant G-24073)Lincoln Laboratory, Purchase Order DDL B-0036

Novel soft bending actuator based power augmentation hand exoskeleton controlled by human intention

This article presents the development of a soft material power augmentation wearable robot using novel bending soft artificial muscles. This soft exoskeleton was developed as a human hand power augmentation system for healthy or partially hand disabled individuals. The proposed prototype serves healthy manual workers by decreasing the muscular effort needed for grasping objects. Furthermore, it is a power augmentation wearable robot for partially hand disabled or post-stroke patients, supporting and augmenting the fingers’ grasping force with minimum muscular effort in most everyday activities. This wearable robot can fit any adult hand size without the need for any mechanical system changes or calibration. Novel bending soft actuators are developed to actuate this power augmentation device. The performance of these actuators has been experimentally assessed. A geometrical kinematic analysis and mathematical output force model have been developed for the novel actuators. The performance of this mathematical model has been proven experimentally with promising results. The control system of this exoskeleton is created by hybridization between cascaded position and force closed loop intelligent controllers. The cascaded position controller is designed for the bending actuators to follow the fingers in their bending movements. The force controller is developed to control the grasping force augmentation. The operation of the control system with the exoskeleton has been experimentally validated. EMG signals were monitored during the experiments to determine that the proposed exoskeleton system decreased the muscular efforts of the wearer

Preamble-based Channel Estimation in OFDM/OQAM Systems: A Review

Filter bank-based multicarrier communications (FBMC) have recently attracted increased interest in both wired (e.g., xDSL, PLC) and wireless (e.g., cognitive radio) applications, due to their enhanced flexibility, higher spectral efficiency, and better spectral containment compared to conventional OFDM. A particular type of FBMC, the so-called FBMC/OQAM or OFDM/OQAM system, consisting of pulse shaped OFDM carrying offset QAM (OQAM) symbols, has received increasing attention due to, among other features, its higher spectral efficiency and implementation simplicity. It suffers, however, from an imaginary inter-carrier/inter-symbol interference that complicates signal processing tasks such as channel estimation. This paper focuses on channel estimation for OFDM/OQAM systems based on a known preamble. A review of the existing preamble structures and associated channel estimation methods is given, for both single- (SISO) and multiple-antenna (MIMO) systems. The various preambles are compared via simulations in both mildly and highly frequency selective channels.Comment: This is an early version of a paper to appear in Signal Processing (Elsevier

Analytical Estimation of the Electrostatic Field in Cylinder-Plane and Cylinder-Cylinder Electrode Configurations

This work presents analytical formulas for the estimation of the electrostatic field in cylinder-plane and cylinder-cylinder electrode configurations. Assuming a predefined potential difference between the electrodes and given their geometrical characteristics, these could be useful for the solution of numerous problems involving such electrode sets. Moreover, the voltage distribution around the electrodes is defined by providing equations either for the equipotentials at a given voltage ratio, or the exact estimation of the potential at any point in the surrounding space. Simplified expressions for critical engineering parameters such as the peak electric field and the field enhancement factor are also given

Compressed collagen and decellularized tissue: novel components in a pipeline approach for the study of cancer metastasis

Metastasis is a complex process which is difficult to study and model. Experimental ingenuity is therefore essential when seeking to elucidate the biological mechanisms involved. Typically, in vitro models of metastasis have been overly simplistic, lacking the characteristic elements of the tumour microenvironment, whereas in vivo models are expensive, requiring specialist resources. Here we propose a pipeline approach for the study of cell migration and colonization, two critical steps in the metastatic cascade.We used a range of extracellular matrix derived contexts to facilitate a progressive approach to the observation and quantification of cell behaviour in 2D, 3D and at border zones between dimensions. At the simplest level, cells were set onto collagen-coated plastic or encapsulated within a collagen matrix. To enhance this, a collagen compression technique provided a stiffened, denser substrate which could be used as a 2D surface or to encapsulate cells. Decellularized tissue from the chorioallantoic membrane of the developing chicken embryo was used to provide a more structured, biologically relevant extracellular matrix-based context in which cell behaviour could then be compared with its in vivo counterpart.Cell behaviour could be observed and quantified within each context using standard laboratory techniques of microscopy and immunostaining, affording the opportunity for comparison and contrast of behaviour across the whole range of contexts. In particular, the temporal constraints of the in vivo CAM were removed when cells were cultured on the decellularized CAM, allowing for much longer-term cell colonization and cell-cell interaction.Together the assays within this pipeline provide the opportunity for the study of cell behaviour in a replicable way across multiple environments. The assays can be set up and analysed using easily available resources and standard laboratory equipment. We believe this offers the potential for the detailed study of cell migration and colonization of tissue, essential steps in the metastatic cascade. Also, we propose that the pipeline could be used in the wider arena of cell culture in general with the increasingly more complex contexts allowing cell behaviours and interactions to be explored in a stepwise fashion in an integrated way