Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Helmut Neher"'
Publikováno v:
CRV
Current action recognition algorithms in ice hockey do not fully exploit the temporal cues available in video. To solve this challenge, we introduce a two-stream network utilizing player pose sequences and optical flow features for recognizing hockey
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bf155782886abecbe551d06c258a9322
https://doi.org/10.1109/crv.2019.00032
https://doi.org/10.1109/crv.2019.00032
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030272715
ICIAR (2)
ICIAR (2)
The incidence of severely atypical melanocytic lesions (SAML) has been increasing year after year. Early detection of SAML by skin surveillance followed by biopsy and treatment may improve survival and reduce the burden on health care systems. Discov
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1d6185e08c643a236a6f7e54290bbce4
https://doi.org/10.1007/978-3-030-27272-2_26
https://doi.org/10.1007/978-3-030-27272-2_26
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030272715
ICIAR (2)
ICIAR (2)
In this paper, we present a novel approach called KPTransfer for improving modeling performance for keypoint detection deep neural networks via domain transfer between different keypoint subsets. This approach is motivated by the notion that rich con
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cbdd69b2aa7fa4c500012e460e785546
https://doi.org/10.1007/978-3-030-27272-2_19
https://doi.org/10.1007/978-3-030-27272-2_19
Publikováno v:
CRV
Human pose estimation in ice hockey is one of the biggest challenges in computer vision-driven sports analytics, with a variety of difficulties such as bulky hockey wear, color similarity between ice rink and player jersey and the presence of additio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::629cb2a66452db4bfc153b1053f7da4c
https://doi.org/10.1109/crv.2018.00051
https://doi.org/10.1109/crv.2018.00051
Publikováno v:
CVPR Workshops
Recognizing actions in ice hockey using computer vision poses challenges due to bulky equipment and inadequate image quality. A novel two-stream framework has been designed to improve action recognition accuracy for hockey using three main components
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5d597b2e1bba1c2f745871c57d28eb19
Publikováno v:
CVPR Workshops
A convolutional neural network (CNN) has been designed to interpret player actions in ice hockey video. The hourglass network is employed as the base to generate player pose estimation and layers are added to this network to produce action recognitio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::59a98091c5ed0f550245b13e9d150928
https://doi.org/10.1109/cvprw.2017.17
https://doi.org/10.1109/cvprw.2017.17
Publikováno v:
CRV
Robust place recognition systems are essential for long term localization and autonomy. Such systems should recognize scenes with both conditional and viewpoint changes. In this paper, we present a deep learning based planar omni-directional place re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cb5331a479299e3f500e492908282263
https://doi.org/10.1109/crv.2017.26
https://doi.org/10.1109/crv.2017.26