In this paper, we present a structured literature mapping of the state-of-the-art of vehicular perception methods and approaches using inertial sensors. An in-depth investigation and classification were performed empl...
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Speed bumps are vertical raisings of the road pavement used to force drivers to slow down to ensure greater safety in traffic. However, these obstacles have disadvantages in terms of efficiency and safety, where the p...
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Speed bumps are vertical raisings of the road pavement used to force drivers to slow down to ensure greater safety in traffic. However, these obstacles have disadvantages in terms of efficiency and safety, where the presence of speed bumps can affect travel time and fuel consumption, cause traffic jams, delay emergency vehicles, and cause vehicle damage or accidents when not properly signaled. Due to these factors, the availability of geolocation information for these obstacles can benefit several applications in Intelligent Transportation System (ITS), such as Advanced Driver Assistance Systems (ADAS) and autonomous vehicles, allowing to trace more efficient routes or alert the driver of the presence of the obstacle ahead. Speed bump detection applications described in the literature employ cameras or inertial sensors, represented by accelerometers and gyroscopes. While camera-based solutions are mature with evaluation in different contextual conditions, those based on inertial sensors do not offer multi-contextual analyses, being mostly simple applications of proof of concept, not applicable in real-world scenarios. For this reason, in this work, we propose the development of a reliable speed bump detection model based on inertial sensors, capable of operating reliably in contextual variations: different vehicles, driving styles, and environments in which vehicles can travel to. For the model development and validation, we collect nine datasets with contextual variations, using three different vehicles, with three different drivers, in three different environments, in which there are three different surface types, in addition to variations in conservation state and the presence of obstacles and anomalies. The speed bumps are present in two different pavement types, asphalt and cobblestone. We use the collected data in experiments to evaluate aspects such as the influence of the placement of the sensors for vehicle data collection and the data window size. Afterwar
The neocognitron is a neural model which can recognize a pattern even when it is shifted in position, changed in size, or distorted. However, the complexity of its structure and its algorithm makes it difficult to tun...
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The neocognitron is a neural model which can recognize a pattern even when it is shifted in position, changed in size, or distorted. However, the complexity of its structure and its algorithm makes it difficult to tune its parameters and to specify the detail of its structure. The characteristics of this model are measured as the relationship between the degree of distortion of the input and the tolerance of the model. Computational experiments show that the pyramid has a suitable structure for implementing a neocognitron, provided that the input has a relatively low spatial frequency.< >
Traditional display fashions of housing design mainly depend on static pictures, which are short of the intuition of house space and do not support interaction during design periods. This paper proposes a virtual hous...
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Spline curve and surface play an important role in CAD and computer graphics. In this paper, we propose several extensions of cubic uniform B-spline. Then, we present the extensions of interpolating α-B-spline based ...
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Spline curve and surface play an important role in CAD and computer graphics. In this paper, we propose several extensions of cubic uniform B-spline. Then, we present the extensions of interpolating α-B-spline based on the new B-splines and the singular blending technique. The advantage of the extensions is that they have global and local shape parameters. Furthermore, we also investigate their applications in data interpolation and polygonal shape deformation.
作者：
Creutzburg, ReinerAcademy of Sciences of the G.D.R
Central Institute of Cybernetics and Information Processes International Basic Laboratory for Image Processing and Computer Graphics Kurstrasse 33 P.O.Box 1298 BerlinDDR-1086 Germany
In this paper we investigate the parallel conflict-free access to complete extended q-ary subtrees of complete q-ary trees. Thereby the memory module assignment function S is supposed to be recursively linear and nonl...
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While considering a mirror and light rays coming either from a point source or from infinity,the reflected light rays may have an envelope,called a caustic *** this paper,we study developable surfaces as *** caustic s...
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While considering a mirror and light rays coming either from a point source or from infinity,the reflected light rays may have an envelope,called a caustic *** this paper,we study developable surfaces as *** caustic surfaces,described in a closed form,are also developable surfaces of the same type as the original mirror *** provide efficient,algorithmic computation to find the caustic surface of each of the three types of developable surfaces(cone,cylinder,and tangent surface of a spatial curve).We also provide a potential application of the results in contemporary free-form architecture design.
Human object extraction from infrared image has broad applications, and has become an active research area in imageprocessing community. Combined with chaos differential evolution (CDE) algorithm and morphological op...
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Human object extraction from infrared image has broad applications, and has become an active research area in imageprocessing community. Combined with chaos differential evolution (CDE) algorithm and morphological operators, a novel infrared human target extraction method is proposed based on nonextensive fuzzy entropy. Firstly, the image was transformed into a fuzzy domain by fuzzy membership function, and the image nonextensive fuzzy entropy was constructed. Then, the image was segmented by thresholding based on the maximum entropy principle and the pseudoadditivity rule of nonextensive entropy. In order to reduce the search time of optimal threshold selection, the CDE algorithm was presented. Finally, the object was extracted using morphological operators to denoise, fill cavity on the threshold segmented image. Experimental results show that the proposed method is efficient and requires less computation time.
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