Generation of synthetic training data for object detection in piles

Elvijs Buls; Roberts Kadikis; Ričards Cacurs; Jānis Ārents

doi:10.1117/12.2523203

15 March 2019 Generation of synthetic training data for object detection in piles

Elvijs Buls, Roberts Kadikis, Ričards Cacurs, Jānis Ārents

Proceedings Volume 11041, Eleventh International Conference on Machine Vision (ICMV 2018); 110411Z (2019) https://doi.org/10.1117/12.2523203
Event: Eleventh International Conference on Machine Vision (ICMV 2018), 2018, Munich, Germany

Abstract

Current state-of-the-art object detectors are based on supervised deep learning approaches. These methods require a large amount of annotated training data, which hinders a wider use of these methods in industry. We propose a method for generating synthetic training data for the task of detecting which objects in a pile can be picked up by a robot arm. The method requires few input images, which are used to create annotated images of piles. After training a state-of-theart detector on the synthetic data, we test it on real images. The results show that the model trained in such a way is not a rival to the best object detectors trained on large datasets of real images, but it is good for the specific task of detecting pickable objects in the piles. The main advantage of the proposed training approach is that the existing models can be easily re-trained to work with piles of different objects by personnel who do not specialize in machine learning.

Citation Download Citation

Elvijs Buls, Roberts Kadikis, Ričards Cacurs, and Jānis Ārents "Generation of synthetic training data for object detection in piles", Proc. SPIE 11041, Eleventh International Conference on Machine Vision (ICMV 2018), 110411Z (15 March 2019); https://doi.org/10.1117/12.2523203

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available