Learn More
We present in this paper a novel object tracking system based on 3D contour models. For this purpose , we integrate two complimentary likelihoods, defined on local color statistics and intensity edges, into a common nonlinear estimation problem. The proposed method improves robustness and adaptiv-ity with respect to challenging background and light(More)
We propose a robust methodology for 3D model-based markerless tracking of textured objects in monocular image sequences. The technique is based on mutual information maximization, a widely known criterion for multi-modal image registration, and employs an efficient multires-olution strategy in order to achieve robustness while keeping fast computational(More)
In this paper we present a robot control architecture for learning by imitation which takes inspiration from recent discoveries in action observation/execution experiments with humans and other primates. The architecture implements two basic processing principles: (1) imitation is primarily directed toward reproducing the outcome of an observed action(More)
Developing a robot system that can interact directly with a human instructor in a natural way requires not only highly-skilled senso-rimotor coordination and action planning on the part of the robot, but also the ability to understand and communicate with a human being in many modalities. A typical application of such a system is interactive assembly for(More)
Direct physical human-robot interaction has become a central part in the research field of robotics today. To use the advantages of the potential for humans and robots to work together as a team in industrial settings, the most important issues are safety for the human and an easy way to describe tasks for the robot. In this work, we present an approach of(More)
In this paper we present an efficient and robust real-time system for object contour tracking in image sequences. The developed application partly relies on an optimized implementation of a state-of-the-art curve fitting algorithm, and integrates important additional features in order to achieve robustness while keeping the speed of the main estimation(More)
In this paper we propose a general, object-oriented software architecture for model-based visual tracking. The library is general purpose with respect to object model, estimated pose parameters, visual modalities employed, number of cameras and objects, and tracking methodology. The base class structure provides the necessary building blocks for(More)
In this paper, we present a system for controlling a quadrocopter using both optical and inertial measurements. We show how to use external stereo camera measurements for visual servoing, by onboard fusion at high rates, only natural features provided by the vehicle and without any active marker. In our experiments, we show the accuracy and robustness of(More)
We report results of an interdisciplinary project which aims at endowing a real robot system with the capacity for learning by goal-directed imitation. The control architecture is biologically inspired as it reflects recent experimental findings in action observation/execution studies. We test its functionality in variations of an imitation paradigm in(More)
Multi-sensory data fusion and medical image analysis often pose the challenging task of aligning dense, non-rigid and multi-modal images. However, optical sequences may also present illumination variations and noise. The above problems can be addressed by an invariant similarity measure, such as mutual information. However, in a variational setting convex(More)