The detection of mobile 3-D objects using both stereovision and motion information is considered. First, the authors present an optical flow estimation method based on a multiresolution technique for the matching of c...
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ISBN:
(纸本)0818620579
The detection of mobile 3-D objects using both stereovision and motion information is considered. First, the authors present an optical flow estimation method based on a multiresolution technique for the matching of contour chain points. Then an algorithm of segmentation of the chains using the continuity of the gradient of the apparent velocity is described. A similar algorithm is developed for stereo vision: the segmentation of the chains is performed in function of their 2-D proximity and the continuity of their disparity. These two segmentations are then used to interpret the scene in terms of isolated rigid or deformable objects. Results are shown for two complex real road scenes.
Texturing 3D shapes is of great importance in computer graphics with applications ranging from game design to augmented reality. However, the processes of texture generation are usually tedious, time-consuming and lab...
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Texturing 3D shapes is of great importance in computer graphics with applications ranging from game design to augmented reality. However, the processes of texture generation are usually tedious, time-consuming and labor-intensive. In this paper, we propose an automatic texture generation algorithm for 3D shapes based on conditional Generative Adversarial Networks (cGAN). The core of our algorithm includes sampling the model outline and building a cGAN in order to generate model textures automatically. In particular, we propose a novel edge detection method using 3D model information which can accurately find the outline of the model to improve the quality of the generated texture. Due to the adaptability of the algorithm, our approach is suitable for texture generation for most 3D models. Experimental results show the efficiency of our algorithm which can easily generate high quality model textures.
Road traffic and traffic congestion are major problems worldwide. To avoid such problems surveillance is the most economical technique for monitoring road traffic. Traffic monitoring has become vital to make sure quic...
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imageprocessing is generally presented in a signal and systems environment which is disregarded to some business oriented Informatics Engineering students as heavy mathematical and boring. Only a few of these student...
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Deep Learning (DL) is an interesting and rapidly developing field of research which has been currently utilized as a part of industry and in many disciplines to address a wide range of problems, from image classificat...
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3D face reconstruction is a research hotspot in computer animation, computer games, computervision, and image recognition fields in recent years. It can enhance the virtual reality experience. In this paper, the appr...
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computervision and Real-time imageprocessing is the foundation of many intelligent technologies in the automotive industry. This paper provides an insight into the application of these two technologies in monitoring...
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ISBN:
(纸本)9781728185194
computervision and Real-time imageprocessing is the foundation of many intelligent technologies in the automotive industry. This paper provides an insight into the application of these two technologies in monitoring the level of attention of the drivers. A speed governor for the vehicle is also designed accordingly. A sequence of images of the driver is captured and the level of drowsiness is calculated in real-time by analyzing various facial landmarks. This is then used to assess and set the speed limit of the speed governor. A working prototype is designed and implemented and the results of experimental testing is also discussed in this paper. This work has high social relevance as it helps to significantly reduce the number of accidents on the road due to drowsy drivers.
How to ensure the safety of a locomotive is a crucial problem, when it moves in a curved railway at night. For solving this problem, a new adaptive locomotive headlamp system based on monocular vision is proposed in t...
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ISBN:
(纸本)9789811079863;9789811079856
How to ensure the safety of a locomotive is a crucial problem, when it moves in a curved railway at night. For solving this problem, a new adaptive locomotive headlamp system based on monocular vision is proposed in this paper. The method consists of two key steps. First, a single-camera is provided to capture the tracks in front of the locomotive, and an imageprocessing algorithm is proposed to obtain the key related parameters. Next, combined with the position feedback signal of the headlamps and the parameters obtained in the previous step, an adaptive control method is proposed to rotate the headlamps. By this way, the light emitted from the headlamps will always be on the axis of the railway, thus ensuring the safety of the locomotive.
A novel framework for computing image flow from time-varying imagery is described. This framework offers the following principal advantages. First, it allows estimation of certain types of discontinuous flow fields wi...
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ISBN:
(纸本)0818620579
A novel framework for computing image flow from time-varying imagery is described. This framework offers the following principal advantages. First, it allows estimation of certain types of discontinuous flow fields without any prior knowledge about the location of discontinuities. The flow fields thus recovered are not blurred at motion boundaries. Second, covariance matrices (or alternatively, confidence measures) are associated with the estimate of image flow at each stage of computation. The estimation-theoretic nature of the framework and its ability to provide covariance matrices make it very useful in the context of applications such as incremental estimation of scene-depth using techniques based on Kalman filtering. The framework is used to recover image flow from two image sequences. To illustrate an application, the image-flow estimates and their covariance matrices thus obtained are also used to recover scene depth.
Traffic management is one of the challenging issues that need to be addressed by any urban area, one of which is Tagbilaran City, located at the Province of Bohol, Philippines. Thus, the need to employ measures such a...
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ISBN:
(纸本)9781450377201
Traffic management is one of the challenging issues that need to be addressed by any urban area, one of which is Tagbilaran City, located at the Province of Bohol, Philippines. Thus, the need to employ measures such as traffic surveillance systems is imperative. In such kind of system, vehicle detection is a basic functionality and in this paper, a YOLO-based model is developed to detect a tricycle, which is a unique kind of public transportation. Training of the model is done on images of tricycles, extracted from actual traffic videos of selected intersections and the performance of the model is measured using the average precision. In this case, a 37.91% average precision is generated for tricycles. Increasing the number of annotated images of tricycles in the training dataset will produce a more precise detection model and including more of the other types of common vehicles will generate data that will support any traffic reduction measure.
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