Shader lamps can augment physical objects with projected virtual replications using a camera-projector system, provided that the physical and virtual object are well registered to each other. Precise registration and tracking has been a cumbersome and intrusive process in the past. In this paper, we present a new method for tracking complex-shaped physical objects interactively. In contrast to previous approaches our system is mobile and makes solely use of the projection of the virtual replication to track the physical object and "stick" the projection to it. Our method consists of two stages, a fast pose initialization based on structured light patterns and a non-intrusive frame-by-frame tracking based on features detected in the projection. During the tracking phase, a radiometrically corrected virtual camera view based on the current pose prediction is rendered and compared to the captured image. Matched features are triangulated providing a sparse set of surface points that is robustly aligned to the virtual model. The alignment transformation serves as an input for the new pose prediction. Detailed experiments including the evaluation of the overlay accuracy show that our approach can accurately and robustly track complex objects at interactive rates.

In Spatial Augmented Reality (SAR) applications, real world objects are augmented with virtual content by means of a calibrated camera-projector system. A computer generated model (CAD) of the real object is used to plan the positions where the virtual content is to be projected. It is often the case that the real object deviates from its CAD model, this resulting in misregistered augmentations. We propose a new method to dynamically correct the planned augmentation by accommodating for the unknown deviations in the object geometry. We use a closed loop approach where the projected features are detected in the camera image and deployed as feedback. As a result, the registration misalignment is identified and the augmentations are corrected in the areas affected by the deviation. Our work is especially focused on SAR applications related to the industrial domain, where this problem is omnipresent. We show that our method is effective and beneficial for multiple industrial applications.

We propose a new semi-automatic calibration approach for projector-camera systems that - unlike existing auto-calibration approaches - additionally recovers the necessary global scale by projecting on an arbitrary object of known geometry from one view. Our method therefore combines surface registration with bundle adjustment optimization on points reconstructed from structured light projections. In simulations on virtual data and experiments with real data we demonstrate that our approach estimates the global scale robustly and is furthermore able to improve incorrectly guessed intrinsic and extrinsic calibration parameters.

In the Shader Lamps concept, a projector-camera system augments physical objects with projected virtual textures, provided that a precise intrinsic and extrinsic calibration of the system is available. Calibrating such systems has been an elaborate and lengthy task in the past and required a special calibration apparatus. Self-calibration methods in turn are able to estimate calibration parameters automatically with no effort. However they inherently lack global scale and are fairly sensitive to input data. We propose a new semi-automatic calibration approach for projector-camera systems that - unlike existing auto-calibration approaches - additionally recovers the necessary global scale by projecting on an arbitrary object of known geometry. To this end our method combines surface registration with bundle adjustment optimization on points reconstructed from structured light projections to refine a solution that is computed from the decomposition of the fundamental matrix. In simulations on virtual data and experiments with real data we demonstrate that our approach estimates the global scale robustly and is furthermore able to improve incorrectly guessed intrinsic and extrinsic calibration parameters thus outperforming comparable metric rectification algorithms.

Shader lamps can augment physical objects with projected virtual replications using a camera-projector system, provided that the physical and virtual object are well registered. Precise registration and tracking has been a cumbersome and intrusive process in the past. In this paper, we present a new method for tracking arbitrarily shaped physical objects interactively. In contrast to previous approaches our system is mobile and makes solely use of the projection of the virtual replication to track the physical object and “stick” the projection to it. Our method consists of two stages, a fast pose initialization based on structured light patterns and a non-intrusive frame-by-frame tracking based on features detected in the projection. In the initialization phase a dense point cloud of the physical object is reconstructed and precisely matched to the virtual model to perfectly overlay the projection. During the tracking phase, a radiometrically corrected virtual camera view based on the current pose prediction is rendered and compared to the captured image. Matched features are triangulated providing a sparse set of surface points that is robustly aligned to the virtual model. The alignment transformation serves as an input for the new pose prediction. Quantitative experiments show that our approach can robustly track complex objects at interactive rates.