Boubekeur, TamyCignoni, PaoloEisemann, ElmarGoesele, MichaelKlein, ReinhardRoth, StefanWeinmann, MichaelWimmer, MichaelChiara Eva Catalano and Livio De Luca2016-10-052016-10-052016978-3-03868-011-62312-6124https://doi.org/10.2312/gch.20161378https://diglib.eg.org:443/handle/10.2312/gch20161378The EU FP7 FET-Open project ''Harvest4D: Harvesting Dynamic 3D Worlds from Commodity Sensor Clouds'' deals with the acquisition, processing, and display of dynamic 3D data. Technological progress is offering us a wide-spread availability of sensing devices that deliver different data streams, which can be easily deployed in the real world and produce streams of sampled data with increased density and easier iteration of the sampling process. These data need to be processed and displayed in a new way. The Harvest4D project proposes a radical change in acquisition and processing technology: instead of a goaldriven acquisition that determines the devices and sensors, its methods let the sensors and resulting available data determine the acquisition process. A variety of challenging problems need to be solved: huge data amounts, different modalities, varying scales, dynamic, noisy and colorful data. This short contribution presents a selection of the many scientific results produced by Harvest4D. We will focus on those results that could bring a major impact to the Cultural Heritage domain, namely facilitating the acquisition of the sampled data or providing advanced visual analysis capabilities.Computer Graphics [Computing methodologies]Shape Modeling10.2312/gch.2016137819-22