HASTE: Hierarchical Analysis of Spatial and Temporal Data From intelligent data acquisition via smart data-management to confident prediction


Carolina Wählby, Division of Visual Information and Interaction, Dept. of IT, UU

Andreas Hellander, Division of Scientific Computing, Dept. of IT, UU


Images contain very rich information, and digital cameras combined with image processing and analysis can detect and quantify a range of patterns and processes. The valuable information is however often sparse, and the ever increasing speed at which data is collected results in data-volumes that exceed the computational resources available.

The HASTE project takes a hierarchical approach to acquisition, analysis, and interpretation of image data. We develop computationally efficient measurements for data description, confidence-driven machine learning for determination of interestingness, and a theory and framework to apply intelligent spatial and temporal information hierarchies, distributing data to computational resources and storage options based on low-level image features.