A Lightweight Deep Learning Model for Vehicle Viewpoint Estimation from Dashcam Images
| Autor: | Leonardo Taccari, Fabio Schoen, Simone Magistri, Matteo Simoncini, Luca Bravi, Luca Kubin, Stefano Caprasecca, Douglas Coimbra de Andrade, Francesco Sambo |
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| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Computer science business.industry Deep learning 02 engineering and technology Object (computer science) 020901 industrial engineering & automation Component (UML) 0202 electrical engineering electronic engineering information engineering Benchmark (computing) RGB color model 020201 artificial intelligence & image processing Computer vision Artificial intelligence business |
| Zdroj: | ITSC |
| Popis: | Vehicle viewpoint estimation from vehicle cameras is a crucial component of road scene understanding.In this paper, we propose a deep lightweight method to predict vehicle viewpoint from a single RGB dashcam image. To this aim, we customize and adapt state-of-the-art deep learning techniques for general object viewpoint estimation to the vehicle viewpoint estimation task. Furthermore, we define a novel objective function that takes into account errors at different granularity to improve neural network training. To keep the model lightweight and fast, we rely upon MobileNetV2 as backbone.Tested both on benchmark viewpoint estimation data (Pascal3D+) and on actual vehicle camera data (nuScenes), our method is shown to outperform the state of the art in vehicle viewpoint estimation, in terms of both accuracy and memory footprint. |
| Databáze: | OpenAIRE |
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