Synthetic Data for Semantic Image Segmentation of Imagery of Unmanned Spacecraft

by   William S. Armstrong, et al.

Images of spacecraft photographed from other spacecraft operating in outer space are difficult to come by, especially at a scale typically required for deep learning tasks. Semantic image segmentation, object detection and localization, and pose estimation are well researched areas with powerful results for many applications, and would be very useful in autonomous spacecraft operation and rendezvous. However, recent studies show that these strong results in broad and common domains may generalize poorly even to specific industrial applications on earth. To address this, we propose a method for generating synthetic image data that are labelled for semantic segmentation, generalizable to other tasks, and provide a prototype synthetic image dataset consisting of 2D monocular images of unmanned spacecraft, in order to enable further research in the area of autonomous spacecraft rendezvous. We also present a strong benchmark result (Sørensen-Dice coefficient 0.8723) on these synthetic data, suggesting that it is feasible to train well-performing image segmentation models for this task, especially if the target spacecraft and its configuration are known.


page 1

page 4

page 5

page 7


Algorithms for Semantic Segmentation of Multispectral Remote Sensing Imagery using Deep Learning

Deep convolutional neural networks (DCNNs) have been used to achieve sta...

DynaDog+T: A Parametric Animal Model for Synthetic Canine Image Generation

Synthetic data is becoming increasingly common for training computer vis...

A Bhattacharyya Coefficient-Based Framework for Noise Model-Aware Random Walker Image Segmentation

One well established method of interactive image segmentation is the ran...

Robust 6D Object Pose Estimation with Stochastic Congruent Sets

Object pose estimation is frequently achieved by first segmenting an RGB...

A Survey on Deep Learning Methods for Semantic Image Segmentation in Real-Time

Semantic image segmentation is one of fastest growing areas in computer ...

Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes

During the last half decade, convolutional neural networks (CNNs) have t...

Please sign up or login with your details

Forgot password? Click here to reset