Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Xiaohan Fei"'
Publikováno v:
IEEE Robotics and Automation Letters. 6:3120-3127
We present a method to infer a dense depth map from a color image and associated sparse depth measurements. Our main contribution lies in the design of an annealing process for determining co-visibility (occlusions, disocclusions) and the degree of r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2ea0779faf6c5123a10ba6373fe942de
https://doi.org/10.1109/lra.2021.3062602
https://doi.org/10.1109/lra.2021.3062602
We describe a method to infer dense depth from camera motion and sparse depth as estimated using a visual-inertial odometry system. Unlike other scenarios using point clouds from lidar or structured light sensors, we have few hundreds to few thousand
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::529e672ba648791b6b32150e2e300050
http://arxiv.org/abs/1905.08616
http://arxiv.org/abs/1905.08616
Autor:
Stefano Soatto, Xiaohan Fei
Publikováno v:
Computer Vision – ECCV 2018 ISBN: 9783030012519
ECCV (11)
ECCV (11)
We present a method to populate an unknown environment with models of previously seen objects, placed in a Euclidean reference frame that is inferred causally and on-line using monocular video along with inertial sensors. The system we implement retu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::05c41ebc1c71fcbdc5ed0d608f5034bc
https://doi.org/10.1007/978-3-030-01252-6_19
https://doi.org/10.1007/978-3-030-01252-6_19
Publikováno v:
CVPR
We describe a system to detect objects in three-dimensional space using video and inertial sensors (accelerometer and gyrometer), ubiquitous in modern mobile platforms from phones to drones. Inertials afford the ability to impose class-specific scale
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a822485f6c6ea543231a244eeacd664c
Publikováno v:
Computer Vision – ECCV 2016 ISBN: 9783319464862
ECCV (3)
ECCV (3)
We propose a data structure obtained by hierarchically pooling Bag-of-Words (BoW) descriptors during a sequence of views that achieves average speedups in large-scale loop closure applications ranging from 2 to 20 times on benchmark datasets. Althoug
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4c9364daf41eb94fa485686eaa665c5e
https://doi.org/10.1007/978-3-319-46487-9_20
https://doi.org/10.1007/978-3-319-46487-9_20