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Nearest Neighbor Search (NNS) is employed by many computer vision algorithms. The computational complexity is large and constitutes a challenge for real-time capability. The basic problem is in rapidly processing a huge amount of data, which is often addressed by means of highly sophisticated search methods and parallelism. We show that NNS based vision algorithms like the Iterative Closest Points algorithm (ICP) can achieve real-time capability while preserving compact size and moderate energy consumption as it is needed in robotics and many other domains. The approach exploits the concept of general purpose computation on graphics processing units (GPGPU) and is compared to parallel processing on CPU. We apply this approach to the 3D scan registration problem, for which a speed-up factor of 88 compared to a sequential CPU implementation is reported.
We have designed an inexpensive intelligent pedestrian counting system. The pedestrian counting system consists of several counters that can be connected together in a distributed fashion and communicate over the wireless channel. The motion pattern is recorded using a set of passive infrared (PIR) sensors. Each counter has one wireless sensor node that processes the PIR sensor data and transmits it to a base station. Then echo state network, a special kind of recurrent neural network, is used to predict the pedestrian count from the input pattern. The evaluation of the performance of such networks in a novel kind of application is one focus of this work. The counter gave a performance of 80.4% which is better than the commercially available low-priced pedestrian counters. The article reports the experiments we did for analyzing the counterperformance and lists the strengths and limitations of the current implementation. It will also report the preliminary test results obtained by substituting the PIR sensors with low-cost active IR distance sensors which can improve the counter performance further.
The nutrient element calcium
(2009)
Arbeitssicherheit: Allein in Deutschland passieren an Produktionsmaschinen fast täglich schwere Unfälle. Tisch- und Formatkreissägen gehören mit zu den gefährlichsten Maschinen. Informatiker entwickelten nun eine neue Sensortechnik, die solche Unfälle verhindert, indem sie Haut unabhängig von Hautfarbe, Alter und Geschlecht sicher vom Werkstück unterscheidet.