Consistency checks for particle filters

An "inconsistent" particle filter produces - in a statistical sense - larger estimation errors than predicted by the model on which the filter is based. Two test variables are introduced that allow the detection of inconsistent behavior. The statistical properties of the variables are analyzed. Experiments confirm their suitability for inconsistency detection

The Use of Separated Reflection Components in Estimating Geometrical Parameters of Curved Surface Elements

Iterative least-squares estimation, requires accurate reflectance models to retrieve geometrical parameters of curved surface elements from an image projection. We investigate the use of separating the diffuse (body) reflection from the specular (surface) reflection being responsible for image highlights. Experiments show that the (smooth) diffuse component yields the best convergence properties, while the (sharp) specular component can contribute to the improvement of the noise insensitivit

Context dependent learning in neural networks

In this paper an extension to the standard error backpropagation learning rule for multi-layer feed forward neural networks is proposed, that enables them to be trained for context dependent information. The context dependent learning is realised by using a different error function (called Average Risk: AVR) in stead of the sum of squared errors (SQE) normally used in error backpropagation and by adapting the update rules. It is shown that for applications where this context dependent information is important, a major improvement in performance is obtained

Towards automated visual flexible endoscope navigation

Background:\ud The design of flexible endoscopes has not changed significantly in the past 50 years. A trend is observed towards a wider application of flexible endoscopes with an increasing role in complex intraluminal therapeutic procedures. The nonintuitive and nonergonomical steering mechanism now forms a barrier in the extension of flexible endoscope applications. Automating the navigation of endoscopes could be a solution for this problem. This paper summarizes the current state of the art in image-based navigation algorithms. The objectives are to find the most promising navigation system(s) to date and to indicate fields for further research.\ud Methods:\ud A systematic literature search was performed using three general search terms in two medical–technological literature databases. Papers were included according to the inclusion criteria. A total of 135 papers were analyzed. Ultimately, 26 were included.\ud Results:\ud Navigation often is based on visual information, which means steering the endoscope using the images that the endoscope produces. Two main techniques are described: lumen centralization and visual odometry. Although the research results are promising, no successful, commercially available automated flexible endoscopy system exists to date.\ud Conclusions:\ud Automated systems that employ conventional flexible endoscopes show the most promising prospects in terms of cost and applicability. To produce such a system, the research focus should lie on finding low-cost mechatronics and technologically robust steering algorithms. Additional functionality and increased efficiency can be obtained through software development. The first priority is to find real-time, robust steering algorithms. These algorithms need to handle bubbles, motion blur, and other image artifacts without disrupting the steering process

Time-of-flight estimation using extended matched filtering

The problem considered is the estimation of the ToF (time-of-flight) of an acoustic tone burst in a reflective environment. Secondary echoes cause a complex interference pattern. Only the ToF of the first echo is of interest. Conventional matched filtering (MF) cannot cope with overlapping echoes. An explicit model for overlapping echoes leads to a generalized MF consisting of a parallel bank of filters rather than just a single filter. The new method is evaluated with a dataset of 150 records of observed waveforms using 3-fold cross validation

Robustness of ToF estimators - an Empirical Evaluation

The performance of ToF estimators for acoustic tone bursts is empirically evaluated. In indoor applications, the observed waveform is likely to be disrupted by multiple echoes. These echoes can cause complex interference patterns. The paper presents the results of a comparison study of the robustness of various ToF estimators against such type of disruptions

Numerical optimisation in spot detector design

Spots are image details resulting from objects, the projections of which are so small that the inner structure of these objects cannot be resolved from their image. Spot detectors are image operators aiming at the detection and localisation of spots in the image. Most spot detectors can be tuned with parameters. This paper addresses the problem of how to select the parameters. We propose to use carefully designed test images, a performance measure, and numerical optimisation techniques to solve this problem. Several optimisation methods are compared, and their adequacy for spot detector design is tested

One-shot 3d surface reconstruction from instantaneous frequencies: solutions to ambiguity problems

Phase-measuring profilometry is a well known technique for 3D surface reconstruction based on a sinusoidal pattern that is projected on a scene. If the surface is partly occluded by, for instance, other objects, then the depth shows abrupt transitions at the edges of these occlusions. This causes ambiguities in the phase and, consequently, also in the reconstruction.\ud This paper introduces a reconstruction method that is based on the instantaneous frequency instead of phase. Using these instantaneous frequencies we present a method to recover from ambiguities caused by occlusion. The recovery works under the condition that some surface patches can be found that are planar. This ability is demonstrated in a simple example. \u

Comparative study of Cl₂, Cl₂/O₂, and Cl₂/N₂ inductively coupled plasma processes for etching of high-aspect-ratio photonic-crystal holes in InP

An extensive investigation has been performed on inductively coupled plasmaetching of InP. An important motivation for this work is the fabrication of high-aspect-ratio holes for photonic crystals. The essential chemistry is based on Cl₂ with the addition of N₂ or O₂ for sidewall passivation. The influence of different process parameters such as gas flows, temperature,pressure, ion energy, and inductively coupled plasma power on the hole geometry is presented. It is concluded that photonic crystals can be etched with Cl₂ only; however, temperature and pressure control is critical. Adding passivation gases largely broadens the window in the parameter space for hole etching. Most importantly, etching of narrow holes can be carried out at higher temperatures where the etching is mass limited and spontaneous etching of InP by Cl₂ occurs.Part of this research is supported by NanoNed, a technology program of the Dutch Ministry of Economic Affairs

Image segmentation and feature extraction for recognizing strokes in tennis game videos

This paper addresses the problem of recognizing human actions from video. Particularly, the case of recognizing events in tennis game videos is analyzed. Driven by our domain knowledge, a robust player segmentation algorithm is developed real video data. Further, we introduce a number of novel features to be extracted for our particular application. Different feature combinations are investigated in order to find the optimal one. Finally, recognition results for different classes of tennis strokes using automatic learning capability of Hidden Markov Models (HMMs) are presented. The experimental results demonstrate that our method is close to realizing statistics of tennis games automatically using ordinary TV broadcast videos