Self-adaptation for mobile robot algorithms using organic computing principles
ARCS'13 Proceedings of the 26th international conference on Architecture of Computing Systems
3D attention: measurement of visual saliency using eye tracking glasses
CHI '13 Extended Abstracts on Human Factors in Computing Systems
Efficient keyframe-based real-time camera tracking
Computer Vision and Image Understanding
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We present a novel and general optimisation framework for visual SLAM, which scales for both local, highly accurate reconstruction and large-scale motion with long loop closures. We take a two-level approach that combines accurate pose-point constraints in the primary region of interest with a stabilising periphery of pose-pose soft constraints. Our algorithm automatically builds a suitable connected graph of keyposes and constraints, dynamically selects inner and outer window membership and optimises both simultaneously. We demonstrate in extensive simulation experiments that our method approaches the accuracy of offline bundle adjustment while maintaining constant-time operation, even in the hard case of very loopy monocular camera motion. Furthermore, we present a set of real experiments for various types of visual sensor and motion, including large scale SLAM with both monocular and stereo cameras, loopy local browsing with either monocular or RGB-D cameras, and dense RGB-D object model building.