Abstract
Target To construct a method for generating object detection dataset based on the virtual environment. The generated dataset can be used for object detection tasks based on deep learning algorithms. Methods The procedural generation method was used to create the city's virtual environment, and also computer graphics were used for rendering and automatic labeling. Results We constructed a virtual reality environment and collected 1500 images through the virtual environment, including 1307 images containing valid vehicle and pedestrian information, and trained a deep learning model based on this dataset. Conclusions A virtual reality environment is successfully created, and the generated dataset can be used to train deep learning object detection algorithms, and the trained models can also effectively perform object detection in real world.
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Ding, P., Shen, Q., Huang, T., Wang, M. (2020). A Generation Method and Verification of Virtual Dataset. In: Long, S., Dhillon, B.S. (eds) Man-Machine-Environment System Engineering. MMESE 2020. Lecture Notes in Electrical Engineering, vol 645. Springer, Singapore. https://doi.org/10.1007/978-981-15-6978-4_55
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DOI: https://doi.org/10.1007/978-981-15-6978-4_55
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