Experiences with an interactive museum tour-guide robot
Artificial Intelligence - Special issue on applications of artificial intelligence
Improved Occupancy Grids for Map Building
Autonomous Robots
Genetic programming for robot vision
ICSAB Proceedings of the seventh international conference on simulation of adaptive behavior on From animals to animats
Dynamic 3D Maps and Their Texture-Based Design
CGI '00 Proceedings of the International Conference on Computer Graphics
Mean Shift Analysis and Applications
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Occupancy grids: a probabilistic framework for robot perception and navigation
Occupancy grids: a probabilistic framework for robot perception and navigation
Map Building Using Cheap Digital Cameras
DICTA '07 Proceedings of the 9th Biennial Conference of the Australian Pattern Recognition Society on Digital Image Computing Techniques and Applications
Multicamera People Tracking with a Probabilistic Occupancy Map
IEEE Transactions on Pattern Analysis and Machine Intelligence
A New Method for Robust and Efficient Occupancy Grid-Map Matching
IbPRIA '07 Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II
Polly: a vision-based artificial agent
AAAI'93 Proceedings of the eleventh national conference on Artificial intelligence
Hierarchical SLAM: Real-Time Accurate Mapping of Large Environments
IEEE Transactions on Robotics
The estimation of the gradient of a density function, with applications in pattern recognition
IEEE Transactions on Information Theory
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This paper presents an approach that uses planar information (homography matrix) to build a visual 2D occupancy grid map from monocular vision. Initially, a segmentation step is necessary to classify parts of the image in floor or non floor. From this classification is possible to determine which parts of the image are free and which parts of the image are obstacles. Practical results are presented to validate the proposal.