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- Fachbereich - Architektur (22)
- Fachbereich - Wirtschaftswissenschaften (18)
- Intelligente Mensch-Technik-Interaktion (12)
We had already demonstrated a numerical model for the point spread function (PSF) of an optical system that can efficiently model both the experimental measurements and the lens design simulations of the PSF. The novelty lies in the portability and the parameterization of this model, which allow for completely new ways to validate optical systems, which is especially interesting not only for mass production optics such as in the automotive industry but also for ophthalmology. The numerical basis for this model is a nonlinear regression of the PSF with an artificial neural network (ANN). After briefly describing both the principle and the applications of the model, we then discuss two optically important aspects: the spatial resolution and the accuracy of the model. Using mean squared error (MSE) as a metric, we vary the topology of the neural network, both in the number of neurons and in the number of hidden layers. Measurement and simulation of a PSF can have a much higher spatial resolution than the typical pixel size used in current camera sensors. We discuss the influence this has on the topology of the ANN. The relative accuracy of the averaged pixel MSE is below 10 − 4, thus giving confidence that the regression does indeed model the measurement data with good accuracy. This article is only the starting point, and we propose several research avenues for future work.
Training autonomous vehicles requires lots of driving sequences in all situations. Collecting and labeling these drive scenes is a very time-consuming and expensive process. Currently, it is not possible to reuse these drive scenes with different optical properties, because there exists no numerically efficient model for the transfer function of the optical system. We present a numerical model for the point spread function (PSF) of an optical system that can efficiently model both experimental measurements and lens design simulations of the PSF. The numerical basis for this model is a nonlinear regression of the PSF with an artificial neural network. The novelty lies in the portability and the parameterization of this model. We present a lens measurement series, yielding a numerical function for the PSF that depends only on the parameters defocus, field, and azimuth. By convolving existing images and videos with this PSF, we generate images as if seen through the measured lens. The methodology applies to any optical scenario, but we focus on the context of autonomous driving, where the quality of the detection algorithms depends directly on the optical quality of the used camera system. With this model, it is possible to reuse existing recordings, with the potential to avoid millions of test drive miles. The parameterization of the optical model allows for a method to validate the functional and safety limits of camera-based advanced driver assistance systems based on the real, measured lens actually used in the product.
In a previous work we have demonstrated a novel numerical model for the point spread function (PSF) of an optical system that can efficiently model both experimental measurements and lens design simulations of the PSF. The novelty lies in the portability and the parameterization of this model, which allows for completely new ways to validate optical systems, which is especially interesting for mass production optics like in the automotive industry, but also for ophtalmology. The numerical basis for this model is a non-linear regression of the PSF with an artificial neural network (ANN). In this work we examine two important aspects of this model: the spatial resolution and the accuracy of the model. Measurement and simulation of a PSF can have a much higher resolution then the typical pixel size used in current camera sensors, especially those for the automotive industry. We discuss the influence this has on on the topology of the ANN and the final application where the modeled PSF is actually used. Another important influence on the accuracy of the trained ANN is the error metric which is used during training. The PSF is a distinctly non-linear function, which varies strongly over field and defocus, but nonetheless exhibits strong symmetries and spatial relations. Therefore we examine different distance and similarity measures and discuss its influence on the modeling performance of the ANN.
Land of High Hopes
(2019)
We are living in the era of sophisticated, state-of-the-art technology, artificial intelligence, accelerating data sciences at ultimate speed and sheer unlimited possibilities. We are able to shoot unmanned rockets equipped with vehicles into the orbit. We can afford to spend fortunes on research and development. However, and that leaves me bloodcurdling and furious, we haven´t managed yet to settle at least some of the most pressing global humanitarian needs: access to food, water, electricity, education and healthcare. So how can we be proud of any achievements? What does make us proud anyway?! ...
Design of a Helical Keyboard
(1996)
Inspired by the cyclical nature of octaves and helical structure of a scale (Shepard, '82 and '83), we prepared a model of a piano-style keyboard (prototyped in Mathematica), which was then geometrically warped into a left-handed helical configuration, one octave/revolution, pitch mapped to height. The natural orientation of upper frequency keys higher on the helix suggests a parsimonious left-handed chirality, so that ascending notes cross in front of a typical listener left to right. Our model is being imported (via the dxf file format) into (Open Inventor/)VRML, where it can be driven by MIDI events, realtime or sequenced, which stream is both synthesized (by a Roland Sound Module), and spatialized by a heterogeneous spatial sound backend (including the Crystal River Engineering Acoustetron II and the Pioneer Sound Field Control speaker-array System), so that the sound of the respective notes is directionalized with respect to sinks, avatars of the human user, by default in the tube of the helix. This is a work-in-progress which we hope to be fully functional within the next few months.
A filtering model for efficient rendering of the spatial image of an occluded virtual sound source
(1999)
Rendering realistic spatial sound imagery for complex virtual environments must take into account the effects of obstructions such as reflectors and occluders. It is relatively well understood how to calculate the acoustical consequence that would be observed at a given observation point when an acoustically opaque object occludes a sound source. But the interference patterns generated by occluders of various geometries and orientations relative to the virtual source and receiver are computationally intense if accurate results are required. In many applications, however, it is sufficient to create a spatial image that is recognizable by the human listener as the sound of an occluded source. In the interest of improving audio rendering efficiency, a simplified filtering model was developed and its audio output submitted to psychophysical evaluation. Two perceptually salient components of occluder acoustics were identified that could be directly related to the geometry and orientation of a simple occluder. Actual occluder impulse responses measured in an anechoic chamber resembled the responses of a model incorporating only a variable duration delay line and a low-pass filter with variable cutoff frequency.
Digital broadcasting enables interactive \sc tv, which presents new challenges for interactive content creation. Besides the technology for streaming and viewing, tools and systems are under development that extend traditional \sc tv studios with virtual set environments. This presentation reviews current technology and describes the requirements for such systems. Interoperability over the production, streaming, and viewer levels requires open interfaces. As the technology allow more interaction, it becomes inherent difficult to control the quality of the viewers experience
High dynamic range environments maps based on still images or video streams are used for computer animation or interactive systems. The task of realistic light setup of scenes using captured environment maps might be eased as well as the visual quality improves. In this article, we discuss the light setting problem for virtual studio (tv) layout and system become more complex to handle this new feature of studio light capturing. The analysis of system requirements identifies the technical challenges.