Martin Stommel

Learn More
3D environment reconstruction is a basic task, delivering the data for mapping, localization and navigation in mobile robotics. We present a new technique that combines a stereo-camera system with a PMD-camera. Both systems generate distance images of the environment but with different characteristics. It is shown that each system compensates effectively(More)
A face recognition system for simultaneous detection and pose estimation is presented. The algorithm proceeds in two steps: At first, separate face components such as eyes, nose and mouth are detected. This is done by a classification of modified SIFT features that are more robust to spatial displacements. Secondly, face-like part constellations are(More)
It is shown that distance computations between SIFT-descriptors using the Euclidean distance suffer from the curse of dimensionality. The search for exact matches is less affected than the generalisation of image patterns, e.g. by clustering methods. Experimental results indicate that for the case of generalisation, the Hamming distance on binarised(More)
This article presents a SIFT-based object recognition method that avoids the typical problems of time-consuming code-book generation and curse of dimensionality in feature comparison. The first problem is solved by using an alphabet of completely synthetic feature vectors. The second problem is solved by using the Hamming-distance on binarised(More)
SIFT features have become extremely popular in computer vision because of their reliable matching qualities under changing lighting conditions. In Robotics they are ubiquitious in self localisation and mapping (SLAM), object tracking and recognition. However, the length of the descriptor is a major obstacle for real-time applications and mobile platforms(More)
In this paper an appearance based, compositional approach to the recognition of deformable objects is presented. First, a hierarchical object model is proposed. On different levels of abstraction the model represents object categories, different views of an object, the parts of an object and basic feature vectors. Then, a training method based on multiple(More)
This paper describes a method to recognize and classify complex objects in digital images. To this end, a uniform representation of prototypes is introduced. The notion of a prototype describes a set of local features which allow to recognize objects by their appearance. During a training step a genetic algorithm is applied to the prototypes to optimize(More)
This paper analyzes the application of machine learning techniques to the control of a soft, peristaltic, xy-sorting table. In particular, we address peristaltic tables made of a soft upper silicone layer and actuated by an array of integrated air-filled chambers. The chambers are pneumatically inflated in order to deform the table and move objects on the(More)