Martin Ahrnbom

According to our database, Martin Ahrnbom authored at least 10 papers between 2016 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of five.

2022

Computer Vision for Automated Traffic Safety Assessment: A Machine Learning Approach.

Martin Ahrnbom

PhD thesis, 2022

Monocular Estimation of Translation, Pose and 3D Shape on Detected Objects using a Convolutional Autoencoder.

Ivar Persson, Martin Ahrnbom, Mikael G. Nilsson

Proceedings of the 17th International Joint Conference on Computer Vision, 2022

Seg2Pose: Pose Estimations from Instance Segmentation Masks in One or Multiple Views for Traffic Applications.

Martin Ahrnbom, Ivar Persson, Mikael G. Nilsson

Proceedings of the 17th International Joint Conference on Computer Vision, 2022

Generalized Urban Traffic Surveillance (GUTS): World-Coordinate Tracking for Traffic Safety Applications.

Martin Ahrnbom, Ivar Persson, Håkan Ardö, Mikael G. Nilsson

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

Height Normalizing Image Transform for Efficient Scene Specific Pedestrian Detection.

Håkan Ardö, Martin Ahrnbom, Mikael G. Nilsson

Proceedings of the 18th IEEE International Conference on Advanced Video and Signal Based Surveillance, 2022

2021

Real-time and Online Segmentation Multi-target Tracking with Track Revival Re-identification.

Martin Ahrnbom, Mikael G. Nilsson, Håkan Ardö

Proceedings of the 16th International Joint Conference on Computer Vision, 2021

2020

Calibration and Absolute Pose Estimation of Trinocular Linear Camera Array for Smart City Applications.

Martin Ahrnbom, Mikael G. Nilsson, Håkan Ardö, Kalle Åström, Oksana Yastremska-Kravchenko, Aliaksei Laureshyn

Proceedings of the 25th International Conference on Pattern Recognition, 2020

2018

A Search Space Strategy for Pedestrian Detection and Localization in World Coordinates.

Mikael G. Nilsson, Martin Ahrnbom, Håkan Ardö, Aliaksei Laureshyn

Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018), 2018

2017

Improving a Real-Time Object Detector with Compact Temporal Information.

Martin Ahrnbom, Morten Borno Jensen, Kalle Åström, Mikael G. Nilsson, Håkan Ardö, Thomas B. Moeslund

Proceedings of the 2017 IEEE International Conference on Computer Vision Workshops, 2017

2016

Fast Classification of Empty and Occupied Parking Spaces Using Integral Channel Features.

Martin Ahrnbom, Kalle Åström, Mikael G. Nilsson

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2016