TB-Places: A Data Set for Visual Place Recognition in Garden Environments

Autor: Maria Leyva-Vallina, Nicola Strisciuglio, Manuel Lopez Antequera, Radim Tylecek, Michael Blaich, Nicolai Petkov

Publikováno v: IEEE Access, Vol 7, Pp 52277-52287 (2019)

Place recognition can be achieved by identifying whether a pair of images (a labeled reference image and a query image) depict the same place, regardless of appearance changes due to different viewpoints or lighting conditions. It is an important com

Externí odkaz: https://doaj.org/article/9436b62c43194789bbec29d8646f46bd

Consistent Semantic Annotation of Outdoor Datasets via 2D/3D Label Transfer

Autor: Radim Tylecek, Robert B. Fisher

Publikováno v: Sensors, Vol 18, Iss 7, p 2249 (2018)

The advance of scene understanding methods based on machine learning relies on the availability of large ground truth datasets, which are essential for their training and evaluation. Construction of such datasets with imagery from real sensor data ho

Externí odkaz: https://doaj.org/article/0a77cfc9c46e4eb7a386383326f525a2

Real-time Stereo Visual Servoing for Rose Pruning with Robotic Arm

Autor: Angelo Mencarelli, Radim Tylecek, Robert B. Fisher, Bart van Tuijl, Hanz Cuevas-Velasquez, Antonio-Javier Gallego, Jochen Hemming

Publikováno v: Cuevas Velasquez, H, Gallego, A-J, Tylecek, R, Hemming, J, van Tuijl, B, Mencarelli, A & Fisher, R B 2020, Real-time Stereo Visual Servoing for Rose Pruning with Robotic Arm . in 2020 IEEE International Conference on Robotics and Automation (ICRA) . Institute of Electrical and Electronics Engineers (IEEE), pp. 7050-7056, 2020 International Conference on Robotics and Automation, Virtual conference, France, 31/05/20 . https://doi.org/10.1109/ICRA40945.2020.9197272
ICRA

The paper presents a working pipeline which integrates hardware and software in an automated robotic rose cutter. To the best of our knowledge, this is the first robot able to prune rose bushes in a natural environment. Unlike similar approaches like

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f242134d2684002450c5ee6f65425287
https://doi.org/10.1109/icra40945.2020.9197272

Hybrid Multi-camera Visual Servoing to Moving Target

Autor: Hanz Cuevas-Velasquez, Marcelo Saval-Calvo, Nanbo Li, Radim Tylecek, Robert B. Fisher

Publikováno v: IROS
Cuevas Velasquez, H, Li, N, Tylecek, R, Fisher, R & Saval-Calvo, M 2019, Hybrid Multi-camera Visual Servoing to Moving Target . in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2018) . Institute of Electrical and Electronics Engineers (IEEE), Madrid, Spain, pp. 1132-1137, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems, Madrid, Spain, 1/10/18 . https://doi.org/10.1109/IROS.2018.8593652
2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Visual servoing is a well-known task in robotics. However, there are still challenges when multiple visual sources are combined to accurately guide the robot or occlusions appear. In this paper we present a novel visual servoing approach using hybrid

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a7b046436d6c178972a9be57893e41e1
http://arxiv.org/abs/1803.02285

SDF-MAN: Semi-Supervised Disparity Fusion with Multi-Scale Adversarial Networks

Autor: Runzi Song, Nanbo Li, Robert B. Fisher, Radim Tylecek, Can Pu

Publikováno v: Pu, C, Song, R, Tylecek, R, Li, N & Fisher, R 2019, ' SDF-MAN: Semi-supervised Disparity Fusion with Multi-scale Adversarial Networks ', Remote Sensing, vol. 11, no. 5, 487 . https://doi.org/10.3390/rs11050487
Remote Sensing; Volume 11; Issue 5; Pages: 487
Remote Sensing, Vol 11, Iss 5, p 487 (2019)

Refining raw disparity maps from different algorithms to exploit their complementary advantages is still challenging. Uncertainty estimation and complex disparity relationships among pixels limit the accuracy and robustness of existing methods and th

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5422184b366bcfccf0b3192bb3d33f06
https://doi.org/10.3390/rs11050487