Tracking without Feature Detection
نویسندگان
چکیده
The tracking method presented in this paper is based on an active-contour algorithm for pose refinement. The most important innovation with respect to most active-contour methods is that no ”features” are detected at any stage: the goodness-of-fit measure for the model is a smooth function (without thresholds) of both model parameters and image grey-levels. This smoothness leads to an estimate of the covariance of the likelihood of the model parameters. This covariance estimate is used for efficient pose optimisation by a Newton-like method and for proper weighting of the innovation in a Kalman filter. The method is demonstrated by tracking motor vehicles with 3-D models.
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