Gerald Schweighofer

Learn More
In theory, the pose of a calibrated camera can be uniquely determined from a minimum of four coplanar but noncollinear points. In practice, there are many applications of camera pose tracking from planar targets and there is also a number of recent pose estimation algorithms which perform this task in real-time, but all of these algorithms suffer from pose(More)
We present a novel and fast algorithm to solve the Perspective-n-Point problem. The PnP problem estimating the pose of a calibrated camera based on measurements and known 3D scene, is recasted as a minimization problem of the Object Space Cost. Instead of limiting the algorithm to perspective cameras, we use a formulation for general camera models. The(More)
We propose a novel, hybrid SLAM system to construct a dense occupancy grid map based on sparse visual features and dense depth information. While previous approaches deemed the occupancy grid usable only in 2D mapping, and in combination with a probabilistic approach, we show that geometric SLAM can produce consistent, robust and dense occupancy(More)
We consider performance evaluation of the state-of the-art solution for recovering the relative pose between two calibrated views. Our focus is on planar scenes which are not tractable by algorithms which do not enforce the so-called calibrated constraint. The capability to cope with planar scenes has therefore been stressed as an important advantage of the(More)
Building a dense and accurate environment model out of range image data faces problems like sensor noise, extensive memory consumption or computation time. We present an approach which reconstructs 3D environments using a probabilistic occupancy grid in real-time. Operating on depth image pyramids speeds up computation time, whereas a weighted interpolation(More)
We study the influence of numerical conditioning on the accuracy of two closed-form solutions to the overconstrained relative orientation problem. We consider the well known eight-point algorithm and the recent five-point algorithm, and evaluate changes in their performance due to Hartley's normalization and Muehlich's equilibration. The need for numerical(More)
This paper presents a novel algorithm to solve the Structure and Motion problem. The novelty is in the use of a general camera model, which does not constrain the algorithm to a specific camera, and the use of the Object Space Error for General Camera Models as cost function. We show that, using this cost function, the structure and the translation part of(More)
The emerging discipline of cognitive vision requires a proper representation of visual information including spatial and temporal relationships, scenes, events, semantics and context. This review article summarizes existing representational schemes in computer vision which might be useful for cognitive vision, and discusses promising future research(More)
This paper presents a novel algorithm for online structure and motion estimation. The algorithm works for general camera models and minimizes object space error, it does not rely on gradient-based optimization, and it is provably globally convergent. In comparison to previous work, which reports cubic complexity in the number of frames, our major(More)
In the European cognitive vision project VAMPIRE (IST2001-34401), mobile AR-kits are used for interactive teaching of a visual active memory. This is achieved by 3D augmented pointing, which combines inside-out tracking for head pose recovery and 3D stereo HCI in an office environment. An artificial landmark is used to establish a global coordinate system,(More)