Machine Learning for Visual Navigation and Localization

Navigation and localization are principal challenges in Robot Vision, where the task is to estimate the geometric relation between a vehicle and its environment, either passively in a virtual model or actively through controlling the robot.

Computer vision Localization at sea using a 360 camera and deep learning for horizon matching.In the active case, the vehicle pose needs to be estimated in real-time, which is achieved by online learning of vision-based regression. To achieve this, problem knowledge and suitable visual representations are combined using machine learning.

Application scenario within WASP where the developed code has been used for people tracking:

Researchers

Fahad Khan

Associate Professor, Docent

Michael Felsberg

Professor, Head of Division

External partner

Saab Group

Publications

A selection of three papers

Bertil Grelsson, Michael Felsberg, Folke Isaksson (2016)

Highly Accurate Attitude Estimation via Horizon Detection

Journal of Field Robotics , Vol.33 , s.967-993 Continue to DOI

Kristoffer Öfjäll, Michael Felsberg, Andreas Robinson (2016)

Visual Autonomous Road Following by Symbiotic Online Learning

Intelligent Vehicles Symposium (IV), 2016 IEEE , s.136-143 Continue to DOI

Michael Felsberg (2018)

Probabilistic and biologically inspired feature representations

WASP research at CVL

Visual Object Tracking

Visual Object Tracking is one of the principal challenges in Computer Vision, where the task is to locate a certain object in all frames of a video, given only its location in the first frame.

A Detailed Framework for Semantic Description of Humans

Semantic description of humans in images and videos is one of the fundamental problems in computer vision with applications such as visual surveillance, facial verification, health care, image and video search engines and human-computer interaction.

Point Cloud Processing

With the growing availability of depth cameras and lidar, the processing of the resulting point clouds has become its own sub-area of Computer Vision.

WASP Computer Vision Laboratory

The research covers a broad range of topics within artificial visual systems with a particular focus on machine learning for robot vision. The group has made major contributions in establishing the concept of computer vision in Sweden.