Review of Trends in Automatic Human Activity Recognition in Vehicle Based in Synthetic Data

• Ana Coimbra ^{[1] [2]} ; Cristiana Neto ^{[1] [2]} ; Diana Ferreira ^{[1] [2]} ; Júlio Duarte ^{[1] [2]} ; Daniela Oliveira ^{[1] [2]} ; Francini Hak ^{[1] [2]} ; Filipe Gonçalves ^[2] ; Joaquim Fonseca ^[2] ; Nicolas Lori ^{[1] [2]} ; António Abelha ^{[1] [2]} ; José Machado ^{[1] [2]}
  1. [1] Universidade do Minho

     Universidade do Minho

     Braga (São José de São Lázaro), Portugal

     
  2. [2] Bosch Car Multimedia (4705-820 Braga, Portugal)
• Localización: Intelligent Data Engineering and Automated Learning – IDEAL 2020. 21st International Conference: Guimarães, Portugal; November 4–6, 2020. Proceedings / Cesar Analide (ed. lit.), Paulo Novais (ed. lit.), David Camacho Fernández (ed. lit.), Hujun Yin (ed. lit.), Vol. 2, 2020 (Part II), ISBN 978-3-030-62365-4, págs. 368-376
• Idioma: inglés
• Enlaces
  • Texto completo
• Resumen

  • Driverless vehicles are more and more becoming a reality. However, people still have some concerns in using them, the main concern is fear, hence the importance of creating a surveillance system inside those vehicles. For the detection and classification of human movements to be possible it is necessary to train the system with data representative enough for all kinds of possibilities. Although the production of large quantities of data becomes an expensive process and adds the problem of data protection, the use of synthetic data once they are artificially generated allows lower costs and eliminates the problem of data protection. A bibliographic study was carried out in this paper with articles from 2017 or later on the use of synthetic data. In these studies, it is noted that synthetic data is widely used with good results. As far as image capture is concerned, they show that 3D cameras have better results, but they are more expensive, so 2D cameras are more often used with later conversion to 3D images. The stitched puppet (SP) model is capable of adapting to the most difficult poses having obtained good results in its application in the FAUST dataset.