Benchmarking of objective quality metrics for point cloud compression
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Capturing high-frequency data concerning the condition of complex systems, e.g. by acoustic monitoring, has become increasingly prevalent. Such high-frequency signals typically contain time dependencies ranging over different time scales and different type ...
Modern information technologies and human-centric communication systems employ advanced content representations for richer portrayals of the real world. The newly adopted imaging modalities offer additional information cues and permit the depiction of real ...
A logconcave likelihood is as important to proper statistical inference as a convex cost function is important to variational optimization. Quantization is often disregarded when writing likelihood models, ignoring the limitations of the physical detectors ...
The measurement and classification of light is essential across many scientific disciplines. Devices used to measure light range from the highly precise scanning spectroradiometers to the more practical compact multichannel filter-array type imaging sensor ...
Learning and compression are driven by the common aim of identifying and exploiting statistical regularities in data, which opens the door for fertile collaboration between these areas. A promising group of compression techniques for learning scenarios is ...
Lossy image compression is a popular, simple and effective solution to reduce the amount of data representing digital pictures. In most lossy compression methods, the reduced volume of data in bits is achieved at the expense of introducing visual artifacts ...
Recent advances in signal processing, machine learning and deep learning with sparse intrinsic structure of data have paved the path for solving inverse problems in acoustics and audio. The main task of this thesis was to bridge the gap between the powerfu ...
The proliferation of phasor measurement units (PMUs) presents new challenges in archiving and processing large amounts of synchrophasor data which necessitates advanced data compression methods. This paper proposes a singular value decomposition (SVD)-base ...
Recent advancements in acquisition of three-dimensional models have been increasingly drawing attention to imaging modalities based on the plenoptic representations, such as light fields and point clouds. Since point cloud models can often contain millions ...
The recent rise in interest in point clouds as an imaging modality has motivated standardization groups such as JPEG and MPEG to launch activities aiming at developing compression standards for point clouds. Lossy compression usually introduces visual arti ...