Golla, TimSchwartz, ChristopherKlein, ReinhardJan Bender and Arjan Kuijper and Tatiana von Landesberger and Holger Theisel and Philipp Urban2014-12-162014-12-162014978-3-905674-74-3https://doi.org/10.2312/vmv.20141271We present a framework for the online compression of incrementally acquired point cloud data. For this, we extend an existing vector quantization-based offline point cloud compression algorithm to handle the challenges that arise from the envisioned online scenario. In particular, we learn a codebook in advance from training data and replace a computationally demanding part of the algorithm with a faster alternative. We show that the compression ratios and reconstruction quality are comparable to the offline version while the speed is sufficiently improved. Furthermore, we investigate how well codebooks that are generated from different amounts of training data generalize to larger sets of point cloud data.E.4 [Coding and Information Theory]Data compaction and compressionI.3.3 [Computer Graphics]Picture/Image GenerationDigitizing and scanningI.4.1 [Image processing and computer vision]Digitizing and Image CaptureQuantization