Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
Computer graphics (2nd ed. in C): principles and practice
Computer graphics (2nd ed. in C): principles and practice
Efficient Region Tracking With Parametric Models of Geometry and Illumination
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fast and Accurate Robot Vision for Vision Based Motion
RoboCup 2000: Robot Soccer World Cup IV
Fast Image Segmentation, Object Recognition and Localization in a RoboCup Scenario
RoboCup-99: Robot Soccer World Cup III
Fast, Accurate, and Robust Self-Localization in the RoboCup Environment
RoboCup-99: Robot Soccer World Cup III
Self-Localization in the RoboCup Environment
RoboCup-99: Robot Soccer World Cup III
A Localization Method for a Soccer Robot Using a Vision-Based Omni-Directional Sensor
RoboCup 2000: Robot Soccer World Cup IV
Clockwork Orange: The Dutch RoboSoccer Team
RoboCup 2001: Robot Soccer World Cup V
Multi-cue Localization for Soccer Playing Humanoid Robots
RoboCup 2006: Robot Soccer World Cup X
A Novel Approach to Efficient Monte-Carlo Localization in RoboCup
RoboCup 2006: Robot Soccer World Cup X
Landmark based global self-localization of mobile soccer robots
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
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This paper describes a two-tiered approach to the self-localization problem for soccer playing robots using generic off-the-shelf color cameras. The solution consists of two layers; the top layer is a global search assuming zero knowledge, and the bottom layer is a local search, assuming a relatively good estimation of the position and orientation of the robot. The global search generally yields multiple candidate positions and orientations, which can be tracked, and assigned a confidence level using the local search and/or historic information.