Zobrazeno 1 - 10
of 39
pro vyhledávání: '"Schauerte, Boris"'
We use Latent-Dynamic Conditional Random Fields to perform skeleton-based pointing gesture classification at each time instance of a video sequence, where we achieve a frame-wise pointing accuracy of roughly 83%. Subsequently, we determine continuous
Externí odkaz:
http://arxiv.org/abs/1510.05879
Autor:
Schauerte, Boris, Stiefelhagen, Rainer
Publikováno v:
PLoS ONE 10 (2015)
It has become apparent that a Gaussian center bias can serve as an important prior for visual saliency detection, which has been demonstrated for predicting human eye fixations and salient object detection. Tseng et al. have shown that the photograph
Externí odkaz:
http://arxiv.org/abs/1501.03383
Autor:
Schauerte, Boris, Zamfirescu, Carol T.
Publikováno v:
In Journal of Discrete Algorithms January 2015 30:13-20
Autor:
Schauerte, Boris
Robotic systems have limited computational capacities. Hence, computational attention models are important to focus on specific stimuli and allow for complex cognitive processing. For this purpose, we developed auditory and visual attention models th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fdd104b6e4d9b1e2bbaa17428d0161c6
Autor:
Chouaieb, Lamia, Ehrenberg, Nikolas, Goddemeier, Niklas, Hauschildt, Daniel, Hegenberg, Jens, Klagges, Daniel, Niedzwiedz, Simon, Schauerte, Boris, Schmidt, Robert, Szcypior, Patrick, Trampisch, Christopher, Walkenhorst, Jens, Wilczek, Adalbert
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::752db9584cbb399ab09cb1afd2ad5ac7
Autor:
Schauerte, Boris
Publikováno v:
Multimodal Computational Attention for Scene Understanding & Robotics; 2016, p9-33, 25p
Autor:
Schauerte, Boris
Publikováno v:
Multimodal Computational Attention for Scene Understanding & Robotics; 2016, p177-180, 4p
Autor:
Schauerte, Boris
Publikováno v:
Multimodal Computational Attention for Scene Understanding & Robotics; 2016, p115-175, 61p