SUSAN—A New Approach to Low Level Image Processing
International Journal of Computer Vision
A critique of structure-from-motion algorithms
Computer Vision and Image Understanding
Monocular model-based 3D tracking of rigid objects
Foundations and Trends® in Computer Graphics and Vision
Three-View Multibody Structure from Motion
IEEE Transactions on Pattern Analysis and Machine Intelligence
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Estimating 3-D structure and camera motion from 2-D image sequences is an important problem in computer vision. In this paper we present an effective approach to tracking and recovery of ego-motion from an image sequence acquired by a single camera attached to a pedestrian. Our approach consists of two stages. In the first phase, human gait analysis is performed and human gait parameters are estimated by frame-by-frame analysis utilising a generalised least squares technique. In the second phase, the gait model is employed within a "predict-correct" framework using a maximum a posteriori expectation maximisation strategy to recover ego-motion and scene structure, while continuously refining the gait model. Experiments on synthetic and real image sequences confirm that the use of the gait model allows for effective tracking while also reducing the computational complexity.