This paper presents an automatic procedure for combining digital images and laser scanner data in order to have a full representation of a scene. In particular, this procedure will serve photogrammetric close range applications such as 3D digital preservation and documentation of cultural heritages by generating highly virtual reality models. Our method is based on a bundle adjustment for the o...

We present a new model-based bundle adjustment algorithm to recover the 3D model of a scene/object from a sequence of images with unknown motions. Instead of representing scene/object by a collection of isolated 3D features (usually points), our algorithm uses a surface controlled by a small set of parameters. Compared with previous modelbased approaches, our approach has the following advantag...

Generating situational awareness by augmenting live imagery with collocated scene information has applications from gameplaying to military command and control. We propose a method of object recognition, reconstruction, and localization using triangulation of SIFT features from keyframe camera poses in a 3D map. The map and keyframe poses themselves are recovered at video-rate by bundle adjustm...

We propose a novel algorithm for the joint refinement of structure and motion parameters from image data directly without relying on fixed and known correspondences. In contrast to traditional bundle adjustment (BA) where the optimal parameters are determined by minimizing the reprojection error using tracked features, the proposed algorithm relies on maximizing the photometric consistency and ...

Bundle Adjustment is a common technique to improve results of any multiple view reconstruction algorithm to obtain 3D structure for computer vision and computer graphics. If the error of a reconstruction can be expressed by an error function, this function can be minimized by numerical methods such as the Levenberg-Marquardt algorithm. By this means, the reconstruction can often be significantl...

In this paper we propose a novel approach to bundle adjustment for large-scale camera configurations. The method does not need to include the 3D points in the optimization as parameters. Additionally, we model the parameters of a camera only relative to a nearby camera to achieve a stable estimation of all cameras. This guarantees to yield a normal equation system with a numerical condition, wh...

We describe the construction of accurate panoramic mosaics from multiple images taken with a rotating camera, or alternatively of a planar scene. The novelty of the approach lies in (i) the transfer of photogrammetric bundle adjustment techniques to mosaicing; (ii) a new representation of image line measurements enabling the use of lines in camera self-calibration, including computation of the ...

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