The paper elaborates on the previous research on the analysis of temporal and spatio-temporal data done in statistical graphics and geo-visualization. We focus on the exploration ...
In this paper, we present a unified framework for reduced space modeling and rendering of dynamic and nonhomogenous participating media, like snow, smoke, dust and fog. The key id...
Spatiotemporal data pose serious challenges to analysts in geographic and other domains. Owing to the complexity of the geospatial and temporal components, this kind of data canno...
Gennady L. Andrienko, Natalia V. Andrienko, Sebast...
In robot navigation tasks, the representation of the surrounding world plays an important role, especially in reinforcement learning approaches. This work presents a qualitative r...
Abstract. In this paper, we describe an unsupervised learning framework to segment a scene into semantic regions and to build semantic scene models from longterm observations of mo...