High-fidelity synthetic images with Unreal Engine, UnrealCV, and a touch of ROS for flavour

Optical Flow Library

Algorithm designed to process the image stream of a high-speed, high-resolution camera (1Mpix at 200+ Hz) online, and provide a useful visual cue such as optical flow to the robot controller.

Geometric computer vision

OpenGV is a C++ library for solving geometric computer vision problems. It contains efficient implementations of absolute-pose, relative-pose, triangulation, and point-cloud alignment methods for the calibrated case.

Point Cloud Library

The Point Cloud Library (PCL) is a standalone, large scale, open project for 2D/3D image and point cloud processing. PCL is released under the terms of the BSD license, and is free for commerical and research use.

Robust and dense visual SLAM for robotic-guided minimally invasive orthopedic procedures

This project aims to develop a vision-based robotic surgical assistant for minimally invasive orthopaedics procedures. The system would be composed of a robotic arm with an attached camera-arthroscope bundle for intra-articular navigation. The system will be capable of a) localizing instruments robustly and reliably inside the human joints; b) generating dense and accurate 3D reconstructed models of the knee joint from intra-articular images,; and c) semi-autonomously navigating the camera (via visual servoing) to follow the surgeons’ tools.

ACRV Picking Benchmark

A physical benchmark for robotic picking: objects, configuration, and overall benchmark rules. Challenges are an important way to drive progress but they occur only occasionally and the test conditions are difficult to replicate outside the challenge. This benchmark is motivated by experience in the recent Amazon Picking Challenge.

QUT Robot Academy

The open online robotics education source. University-level, short video lessons and full online courses to help you understand and prepare for this technology of the future.

What is Deep Learning and How Does It Work?

Tom’s notes on Lie groups

Tom Drummond's notes on the use of Lie Groups and Projective Geometry for Engineering and Computer Vision.

Multiple View Geometry in Computer Vision

The classic introduction to the geometric relationship between the 3D world and 2D image projections.

Towards Robust Grasping and Manipulation Skills for Humanoids

In this workshop, we aim to bring together researchers and experts in key areas for grasping and manipulation such as perception, control, learning, design of hands and grippers, and studies analysing human manipulation skills. We aspire to identify recent developments in these research areas, both in theory and applications, discussing recent achievements, debating underlying assumptions, and challenges for future progress.

Brave new ideas for motion representations in videos II, CVPR 2017

In the late years Deep Learning has been a great force of change on most computer vision tasks. In video analysis problems, however, such as action recognition and detection, motion analysis and tracking, shallow architectures remain surprisingly competitive. What is the reason for this conundrum? Larger datasets are part of the solution.

Workshop on Deep Learning for Robotic Vision, CVPR 2017

Recent advances in deep learning techniques have made impressive progress in many areas of computer vision, including classification, detection, and segmentation. While all of these areas are relevant to robotics applications, robotics also presents many unique challenges which require new approaches.

ICRA 2018 in Brisbane

The International Conference on Robotics and Automation (ICRA) 2018 will be held for the first time in Australia in Brisbane from the 21st to 25th May.

Age of Robotics

DeepMind (Deep Learning and Robotics)

Andrej Karpathy (Deep Learning)

Ferenc Huszár (Deep Learning)

New Deep Learning Supercomputer

Deep learning supercomputer is providing the computer power to train deeper and larger models and to handle large numbers of parameters and big data.

Google Impact Challenge

Centre Researchers Chief Investigator Matt Dunbabin and Research Fellow Feras Dayoub won the people's choice award in the Google Impact Challenge Australia in 2016. The award is worth $750,000. Their project with the Great Barrier Reef Foundation will create a low-cost 'robo reef protector'.