Christoph S. Garbe

Real-Time Motion Estimation and Visualization on Graphics Cards

We present a tool for real-time visualization of motion features in 2D image sequences. The motion is estimated through an eigenvector analysis of the spatio-temporal structure tensor at every pixel location. This approach is computationally demanding but allows reliable velocity estimates as well as quality indicators for the obtained results. We use a 2D color map and a region of interest selector for the visualization of the velocities. On the selected velocities we apply a hierarchical smoothing scheme which allows the choice of the desired scale of the motion field. We demonstrate several examples of test sequences in which some persons are moving with different velocities than others. These persons are visually marked in the real-time display of the image sequence. The tool is also applied to angiography sequences to emphasize the blood flow and its distribution. An efficient processing of the data streams is achieved by mapping the operations onto the stream architecture of standard graphics cards. The card receives the images and performs both the motion estimation and visualization, taking advantage of the parallelism in the graphics processor and the superior memory bandwidth. The integration of data processing and visualization also saves on unnecessary data transfers and thus allows the real-time analysis of 320/spl times/240 images. We expect that on the newest generation of graphics hardware our tool could run in real time for the standard VGA format.

Imaging fluorescence (cross-) correlation spectroscopy in live cells and organisms

Single-plane illumination (SPIM) or total internal reflection fluorescence (TIRF) microscopes can be combined with fast and single-molecule-sensitive cameras to allow spatially resolved fluorescence (cross-) correlation spectroscopy (FCS or FCCS, hereafter referred to FCS/FCCS). This creates a powerful quantitative bioimaging tool that can generate spatially resolved mobility and interaction maps with hundreds to thousands of pixels per sample. These massively parallel imaging schemes also cause less photodamage than conventional single-point confocal microscopy–based FCS/FCCS. Here we provide guidelines for imaging FCS/FCCS measurements on commercial and custom-built microscopes (including sample preparation, setup calibration, data acquisition and evaluation), as well as anticipated results for a variety of in vitro and in vivo samples. For a skilled user of an available SPIM or TIRF setup, sample preparation, microscope alignment, data acquisition and data fitting, as described in this protocol, will take ∼1 d, depending on the sample and the mode of imaging.

Transfer Across the Air-Sea Interface

The efficiency of transfer of gases and particles across the air-sea interface is controlled by several physical, biological and chemical processes in the atmosphere and water which are described here (including waves, large- and small-scale turbulence, bubbles, sea spray, rain and surface films). For a deeper understanding of relevant transport mechanisms, several models have been developed, ranging from conceptual models to numerical models. Most frequently the transfer is described by various functional dependencies of the wind speed, but more detailed descriptions need additional information. The study of gas transfer mechanisms uses a variety of experimental methods ranging from laboratory studies to carbon budgets, mass balance methods, micrometeorological techniques and thermographic techniques. Different methods resolve the transfer at different scales of time and space; this is important to take into account when comparing different results. Air-sea transfer is relevant in a wide range of applications, for example, local and regional fluxes, global models, remote sensing and computations of global inventories. The sensitivity of global models to the description of transfer velocity is limited; it is however likely that the formulations are more important when the resolution increases and other processes in models are improved. For global flux estimates using inventories or remote sensing products the accuracy of the transfer formulation as well as the accuracy of the wind field is crucial.

Estimation of Surface Flow and Net Heat Flux from Infrared Image Sequences

The study of dynamical processes at the sea surface interface using infrared image sequence analysis has gained tremendous popularity in recent years. Heat is transferred by similar transport mechanisms as gases relevant to global climatic changes. These similarities lead to the use of infrared cameras to remotely visualize and quantitatively estimate parameters of the underlying processes. Relevant parameters that provide important evidence about the models of air-sea gas transfer are the temperature difference across the thermal sub layer, the probability density function of surface renewal and the flow field at the surface. Being a driving force in air sea interactions, it is of equal importance to measure heat fluxes. In this paper we will present algorithms to measure the above parameters of air-sea gas transfer during night-time and show how to combine physical modeling and quantitative digital image processing algorithms to identify transport models. The image processing routines rely on an extension of optical flow computations to incorporate brightness changes in a total least squares (TLS) framework. Statistical methods are employed to support a model of gas transfer and estimate its parameters. Measurements in a laboratory environment were conducted and results verified with ground truth data gained from traditional measurement techniques.

Computing range flow from multi-modal Kinect data

In this paper, we present a framework for range flow estimation from Microsofts multi-modal imaging device Kinect. We address all essential stages of the flow computation process, starting from the calibration of the Kinect, over the alignment of the range and color channels, to the introduction of a novel multi-modal range flow algorithm which is robust against typical (technology dependent) range estimation artifacts.

Dual-Color Fluorescence Cross-Correlation Spectroscopy on a Single Plane Illumination Microscope (SPIM-FCCS)

Single plane illumination microscopy based fluorescence correlation spectroscopy (SPIM-FCS) is a new method for imaging FCS in 3D samples, providing diffusion coefficients, flow velocities and concentrations in an imaging mode. Here we extend this technique to two-color fluorescence cross-correlation spectroscopy (SPIM-FCCS), which allows to measure molecular interactions in an imaging mode. We present a theoretical framework for SPIM-FCCS fitting models, which is subsequently used to evaluate several test measurements of in-vitro (labeled microspheres, several DNAs and small unilamellar vesicles) and in-vivo samples (dimeric and monomeric dual-color fluorescent proteins, as well as membrane bound proteins). Our method yields the same quantitative results as the well-established confocal FCCS, but in addition provides unmatched statistics and true imaging capabilities.

An adaptive confidence measure for optical flows based on linear subspace projections

Confidence measures are important for the validation of optical flow fields by estimating the correctness of each displacement vector. There are several frequently used confidence measures, which have been found of at best intermediate quality. Hence, we propose a new confidence measure based on linear subspace projections. The results are compared to the best previously proposed confidence measures with respect to an optimal confidence. Using the proposed measure we are able to improve previous results by up to 31%.

Feature Selection Using Multiobjective Optimization for Named Entity Recognition

Appropriate feature selection is a very crucial issue in any machine learning framework, specially in Maximum Entropy (ME). In this paper, the selection of appropriate features for constructing a ME based Named Entity Recognition (NER) system is posed as a multiobjective optimization (MOO) problem. Two classification quality measures, namely recall and precision are simultaneously optimized using the search capability of a popular evolutionary MOO technique, NSGA-II. The proposed technique is evaluated to determine suitable feature combinations for NER in two languages, namely Bengali and English that have significantly different characteristics. Evaluation results yield the recall, precision and F-measure values of 70.76%, 81.88% and 75.91%, respectively for Bengali, and 78.38%, 81.27% and 79.80%, respectively for English. Comparison with an existing ME based NER system shows that our proposed feature selection technique is more efficient than the heuristic based feature selection.

A Survey on Time-of-Flight Stereo Fusion

Due to the demand for depth maps of higher quality than possible with a single depth imaging technique today, there has been an increasing interest in the combination of different depth sensors to produce a “super-camera” that is more than the sum of the individual parts. In this survey paper, we give an overview over methods for the fusion of Time-of-Flight (ToF) and passive stereo data as well as applications of the resulting high quality depth maps. Additionally, we provide a tutorial-based introduction to the principles behind ToF stereo fusion and the evaluation criteria used to benchmark these methods.

Transport at the Air-Sea Interface

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