2004 · 61 citations · 20 references
ComputingComputer ScienceComputer VisionMachine VisionRobot VisionAugmented RealityMotion EstimationObject RecognitionOcclusion HandlingPose EstimationVisual TrackingInitializationReal-time TrackingRegistration
We present a fully automated approach to camera registration for augmented reality systems. It relies on purely passive vision techniques to solve the initialization and real-time tracking problems, given a rough CAD model of parts of the real scene. It does not require a controlled environment, for example placing markers. It handles arbitrarily complex models, occlusions, large camera displacements and drastic aspect changes. This is made possible by two major contributions: the first one is a fast recognition method that detects the known part of the scene, registers the camera with respect to it, and initializes a real-time tracker, which is the second contribution. Our tracker eliminates drift and jitter by merging the information from preceding frames in a traditional recursive tracking fashion with that of a very limited number of key-frames created off-line. In the rare instances where it fails, for example because of large occlusion, it detects the failure and reinvokes the initialization procedure. We present experimental results on several different kinds of objects and scenes.
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