Physically-based interactive camera motion control using 3D input devices
Related publications (34)
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VR (Virtual Reality) is a real-time simulation that creates the subjective illusion of being in a virtual world.This thesis explores how integrating the user's body and fingers can be achieved and beneficial for the user to experience VR.At the advent of V ...
In our everyday life we interact with the surrounding environment using our hands. A main focus of recent research has been to bring such interaction to virtual objects, such as the ones projected in virtual reality devices, or super-imposed as holograms i ...
Capturing and processing human geometry, appearance, and motion is at the core of computer graphics, computer vision, and human-computer interaction. The high complexity of human geometry and motion dynamics, and the high sensitivity of the human visual sy ...
We investigated how the visual system selects a reference frame for the perception of motion. Two concentric arcs underwent circular motion around the center of the display, where observers fixated. The outer (target) arc's angular velocity profile was mod ...
Association for Research in Vision and Ophthalmology (ARVO)2016
Motion LoD (Level of Detail) is a preprocessing technique that generates multiple details of captured motion by eliminating joints. This LoD technique is applied to movie, game or VR environments for the purpose of improving speed of crowd animation. So fa ...
Dense three-dimensional reconstruction of a scene from images is a very challenging task. In the structure from motion approach one of the key points is to compute depth maps which contain the distance of objects in the scene to a moving camera. Usually, t ...
The aim of this thesis is to build a system able to automatically and robustly track human motion in 3–D starting from monocular input. To this end two approaches are introduced, which tackle two different types of motion: The first is useful to analyze ac ...
Mechanical figures that mimic human motions continue to entertain us and capture our imagination. Creating such automata requires expertise in motion planning, knowledge of mechanism design, and familiarity with fabrication constraints. Thus, automaton des ...
We present a probabilistic approach to learn robust models of human motion through imitation. The association of Hidden Markov Model (HMM), Gaussian Mixture Regression (GMR) and dynamical systems allows us to extract redundancies across multiple demonstrat ...
Institute of Electrical and Electronics Engineers2010
We present a probabilistic approach to learn robust models of human motion through imitation. The association of Hidden Markov Model (HMM), Gaussian Mixture Regression (GMR) and dynamical systems allows us to extract redundancies across multiple demonstrat ...