Tracking of Multiple Targets Using Online Learning for Reference Model Adaptation

2008 ◽  
Vol 38 (6) ◽  
pp. 1465-1475 ◽  
Author(s):  
F. Pernkopf
Keyword(s):  
Online Learning ◽  
Reference Model ◽  
Model Adaptation ◽  
Multiple Targets

Quasi-Facial Communication for Online Learning Using 3D Modeling Techniques

2010 ◽  
pp. 181-191
Author(s):  
Wang Yushun ◽  
Zhuang Yueting
Keyword(s):  
Online Learning ◽  
Reference Model ◽  
Texture Mapping ◽  
Feature Points ◽  
Face Database ◽  
3D Face ◽  
Distant Learning ◽  
Facial Modeling ◽  
The Individual ◽  
3D Face Database

Online interaction with 3D facial animation is an alternative way of face-to-face communication for distance education. 3D facial modeling is essential for virtual educational environments establishment. This article presents a novel 3D facial modeling solution that facilitates quasi-facial communication for online learning. Our algorithm builds 3D facial models from a single image, with support of a 3D face database. First from the image, we extract a set of feature points, which are then used to automatically estimate the head pose parameters using the 3D mean face in our database as a reference model. After the pose recovery, a similarity measurement function is proposed to locate the neighborhood for the given image in the 3D face database. The scope of neighborhood can be determined adaptively using our cross-validation algorithm. Furthermore, the individual 3D shape is synthesized by neighborhood interpolation. Texture mapping is achieved based on feature points. The experimental results show that our algorithm can robustly produce 3D facial models from images captured in various scenarios to enhance the lifelikeness in distant learning.

Quasi-Facial Communication for Online Learning Using 3D Modeling Techniques

2010 ◽  
pp. 727-737
Author(s):  
Yushun Wang ◽  
Yueting Zhuang
Keyword(s):  
Online Learning ◽  
Reference Model ◽  
Texture Mapping ◽  
Feature Points ◽  
Face Database ◽  
3D Face ◽  
Distant Learning ◽  
Facial Modeling ◽  
The Individual ◽  
3D Face Database

Online interaction with 3D facial animation is an alternative way of face-to-face communication for distance education. 3D facial modeling is essential for virtual educational environments establishment. This article presents a novel 3D facial modeling solution that facilitates quasi-facialcommunication for online learning. Our algorithm builds 3D facial models from a single image, with support of a 3D face database. First from the image, we extract a set of feature points, which are then used to automatically estimate the head pose parameters using the 3D mean face in our database as a reference model. After the pose recovery, a similarity measurement function is proposed to locate the neighborhood for the given image in the 3D face database. The scope of neighborhood can be determined adaptivelyusing our cross-validation algorithm. Furthermore, the individual 3D shape is synthesized by neighborhood interpolation. Texture mapping is achieved based on feature points. The experimental results show that our algorithm can robustly produce 3D facial models from images captured in various scenarios to enhance the lifelikeness in distant learning.

scholarly journals Fuzzy Adaptation Algorithms’ Control for Robot Manipulators with Uncertainty Modelling Errors

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Yongqing Fan ◽  
Keyi Xing ◽  
Xiangkui Jiang
Keyword(s):  
Fuzzy Logic ◽  
Online Learning ◽  
Reference Model ◽  
Robot Manipulators ◽  
Fuzzy Logic System ◽  
Fuzzy Rules ◽  
Fuzzy Logic Systems ◽  
Control Scheme ◽  
Logic Systems ◽  
Logic System

A novel fuzzy control scheme with adaptation algorithms is developed for robot manipulators’ system. At the beginning, one adjustable parameter is introduced in the fuzzy logic system, the robot manipulators system with uncertain nonlinear terms as the master device and a reference model dynamic system as the slave robot system. To overcome the limitations such as online learning computation burden and logic structure in conventional fuzzy logic systems, a parameter should be used in fuzzy logic system, which composes fuzzy logic system with updated parameter laws, and can be formed for a new fashioned adaptation algorithms controller. The error closed-loop dynamical system can be stabilized based on Lyapunov analysis, the number of online learning computation burdens can be reduced greatly, and the different kinds of fuzzy logic systems with fuzzy rules or without any fuzzy rules are also suited. Finally, effectiveness of the proposed approach has been shown in simulation example.

Die Spezifität von Begabungsüberzeugungen als Determinante des verbalen und mathematischen Begabungsselbstkonzepts

2002 ◽  
Vol 16 (2) ◽  
pp. 87-97 ◽  
Author(s):  
Jens Möller ◽  
Britta Pohlmann ◽  
Lilian Streblow ◽  
Julia Kaufmann
Keyword(s):  
Reference Model ◽  
Frame Of Reference ◽  
External Frame

Zusammenfassung: Das I/E-Modell (“Internal/External Frame of Reference Model”) von Marsh (1986) postuliert, dass Schülerinnen und Schüler dimensionale Vergleiche der eigenen Leistungen in einem Fach mit den Leistungen in einem anderen Fach anstellen. Diese Vergleiche führen dazu, dass z. B. Schüler mit guten Leistungen in Mathematik ihre verbalen Fähigkeiten niedriger einschätzen. Gegenstand dieser Untersuchung mit N = 1114 Probanden ist die Frage, ob die Überzeugungen von Personen zum Zusammenhang von mathematischer und verbaler Begabung die Effekte dimensionaler Vergleiche moderieren. Analysen zeigten die Bedeutung der Begabungsüberzeugungen der Schülerinnen und Schüler: Negative Zusammenhänge zwischen den Fachleistungen in einem Fach und dem akademischen Selbstkonzept in einem anderen Fach ergaben sich insbesondere für Personen, die annehmen, dass Begabung domänenspezifisch ist, man also entweder mathematisch oder sprachlich begabt ist. Für Schüler mit eher wenig spezifischer Begabungsüberzeugung ergaben sich geringere Effekte dimensionaler Vergleiche.

Eye movement in response to single and multiple targets.

1985 ◽  
Author(s):  
R. V. Kenyon ◽  
Y. Y. Zeevi ◽  
P. A. Wetzel ◽  
L. R. Young
Keyword(s):  
Eye Movement ◽  
Multiple Targets
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