Modeling Traffic Scenes for Intelligent Vehicles Using CNN-Based Detection and Orientation Estimation
| العنوان: | Modeling Traffic Scenes for Intelligent Vehicles Using CNN-Based Detection and Orientation Estimation |
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| المؤلفون: | José María Armingol, David Martin, Carlos Guindel |
| المصدر: | ROBOT 2017: Third Iberian Robotics Conference ISBN: 9783319708355 ROBOT (2) |
| بيانات النشر: | Springer International Publishing, 2017. |
| سنة النشر: | 2017 |
| مصطلحات موضوعية: | business.industry, Computer science, Orientation (computer vision), Deep learning, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, 020302 automobile design & engineering, 02 engineering and technology, Frame rate, Object detection, Field (computer science), Identification (information), 0203 mechanical engineering, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Computer vision, Artificial intelligence, business, Stereo camera |
| الوصف: | Object identification in images taken from moving vehicles is still a complex task within the computer vision field due to the dynamism of the scenes and the poorly defined structures of the environment. This research proposes an efficient approach to perform recognition on images from a stereo camera, with the goal of gaining insight of traffic scenes in urban and road environments. We rely on a deep learning framework able to simultaneously identify a broad range of entities, such as vehicles, pedestrians or cyclists, with a frame rate compatible with the strong requirements of onboard automotive applications. The results demonstrate the capabilities of the perception system for a wide variety of situations, thus providing valuable information to understand the traffic scenario. |
| ردمك: | 978-3-319-70835-5 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::97144660da8e73d37eb1dfd56b377bab https://doi.org/10.1007/978-3-319-70836-2_40 |
| حقوق: | CLOSED |
| رقم الأكسشن: | edsair.doi...........97144660da8e73d37eb1dfd56b377bab |
| قاعدة البيانات: | OpenAIRE |
| ردمك: | 9783319708355 |
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