Authors:
Jan Rus
and
Libor Váša
Affiliation:
University of West Bohemia, Czech Republic
Keyword(s):
Static Triangle Meshes, Dynamic Triangle Meshes, Data Compression, Coddyac, Clustering, Blocking Artifacts, Deblocking, Visual Quality.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Geometric Computing
;
Geometry and Modeling
;
Modeling and Algorithms
Abstract:
Mesh segmentation (clustering) is a useful tool, which improves compression performance. On the other hand, per-partes processing of meshes often leads to new types of artifacts - cracks and shifts on the borders between clusters. These artifacts are detected by both, Human Visual System (HVS) and perceptually-motivated distortion metrics. In this paper, we present a post processing algorithm, which aims at reducing such artifacts without needing any additional data - using only information about the cluster distribution that is already
present at the decoder. A rigid transformation, which minimises the border artifacts, is iteratively computed and applied per cluster. Our experiments show that this approach leads to a reduction of distortion, as measured by the STED metric, by up to 18% for low bitrates. We also present visual results confirming that the improvement is well visible.