Tobias Klinger

A Stereoscopic Approach for the Association of People Tracks in Video Surveillance Systems

analyses (COLLINS et al. 2001). The more accurate the object coordinates of people in the scene are known, the more detailed analyses can be conducted with respect to motion patterns or interactions between tracked people. In this paper we present an approach that generates consistent global tracks of people in non-crowded scenarios. The trajectories are calculated in a common reference frame from observations of multiple surveillance cameras. An important step in our work is the estimation of body height as well as a reliable association of tracks across partly overlapping views. For that purpose, stereoscopic analysis is applied to overlapping parts of images which are either generated randomly while scanning wide areas with several PTZ cam

Antarctic Coastline Detection using Snakes

1 Extended version of a paper published in The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XXXVIII, Part 4, 2010, 7 p. (on CD-ROM). the update cycle of the coastline data is limited by the revisit time of the imaging sensor, and the accuracy of the coastline is influenced by the ground sample distance of the images. The availability of space borne imagery has increased in recent decades due to a larger number of related satellites, including Radarsat-1, Landsat ETM+ or MODIS on board Aqua/Terra.

Metaheuristics for Supervised Parameter Tuning of Multiresolution Segmentation

This letter evaluates metaheuristics for the supervised parameter tuning of multiresolution-region-growing segmentation. Three groups of metaheuristics are tested in terms of convergence speed and solution quality. Generalized pattern search, mesh adaptive direct search, and Nelder-Mead represent the single-solution group. Differential evolution (DE) represents the population group. DE followed by each of the aforementioned single-solution metaheuristics represents the hybrid metaheuristic group. This letter reveals that the optimization objective functions typically have countless local minima, many of them leading to very poor solutions. Experiments on three data sets demonstrated that single-solution-based methods often lead to a solution with unacceptable quality. DE was less susceptible to be stuck in local minima when compared to single-solution methods, but it was slower in reaching the minima. Moreover, hybrid methods presented the best tradeoff between accuracy and convergence speed.

Automated extraction of the Antarctic coastline using snakes

In this paper we present an automatic approach for coastline detection from images which is based on parametric active contours (snakes). Snakes require the definition of an energy functional that reflects the underlying coastline model. As for Antarctica, our application domain, the coastline appearance in the used optical images is heterogeneous. Therefore, a single model does not work equally well in all situations. On the basis of an up-to-date Landsat mosaic three different models are formulated that match a large part of the Antarctic coastline, i.e. the transition from ice shelf to water, from ice shelf to sea ice and from rocky terrain to water. For each of the three different cases the energy terms are optimized based on the radiometric properties of the adjacent regions as well as the curvature and the potential change-rate of the coastline itself. A supervised classification for the three classes ice, water and rocky terrain controls the whole process by choosing the most applicable model for a certain image region. With a view to the practical application the developed approach was integrated into a semiautomatic system, where the human operator supervises the optimization process of the contour and interactively corrects the results if the system fails.