Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Lukas Rybok"'
Autor:
P. Koch, J.M. Pons Perez, E. Pirard, Lukas Rybok, P. Barnabé, P. Teixeira Mendes, C. Garcia Pina, C. Bachmann, J.C. Videira Vazquez
Publikováno v:
Mineral Exploration Symposium.
Publikováno v:
Pattern Recognition Letters. 72:82-90
We analyze the benefits of using high-level semantics for transfer metric learning.We present a hierarchical model based on the embedded structure in attribute space.We propose a novel decorrelated normalized space (DNS) for transfer metric learning.
Publikováno v:
MVA
There is a large interest on performing elderly care monitoring using Computer Vision. It has the potential to provide a better scene understanding than current sensing approaches at an affordable price, but there are still considerable practical cha
Publikováno v:
ICPR
Learning from few examples is considered a very challenging task where transfer learning proved to be beneficial. Such a learning framework exploits previous experiences and knowledge to compensate for the lack of training data in a novel domain. Kno
Publikováno v:
WACV
Object information is an important cue to discriminate between activities that draw part of their meaning from context. Most of current work either ignores this information or relies on specific object detectors. However, such object detectors requir
Autor:
Uwe D. Hanebeck, Peter Krauthausen, Rainer Stiefelhagen, Hildegard Kuehne, Tanja Schultz, Lukas Rybok, Dirk Gehrig
Publikováno v:
IROS
In this paper, a multi-level approach to intention, activity, and motion recognition for a humanoid robot is proposed. Our system processes images from a monocular camera and combines this information with domain knowledge. The recognition works on-l
Publikováno v:
Humanoids
Human action and activity recognition from videos has attracted an increasing number of researchers in recent years. However, most of the works aim at multimedia retrieval and surveillance applications, but rarely at humanoid household robots, even t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::46d63f3e8e78fe84a7aaf4fbdce78018
https://publikationen.bibliothek.kit.edu/1000035121/2619446
https://publikationen.bibliothek.kit.edu/1000035121/2619446
Publikováno v:
ICPR
The knowledge about the body orientation of humans can improve speed and performance of many service components of a smart-room. Since many of such components run in parallel, an estimator to acquire this knowledge needs a very low computational comp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::67ba65acccc5f5c5a970b10b0dbdc33e
https://publikationen.bibliothek.kit.edu/1000026385
https://publikationen.bibliothek.kit.edu/1000026385