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A General Framework for Depth Compression and Multi-Sensor Fusion in Asymmetric View-Plus-Depth 3D Representation

Research output: Contribution to journalArticleScientificpeer-review


Original languageEnglish
Pages (from-to)97516-97528
Number of pages13
JournalIEEE Access
Publication statusPublished - 1 Jan 2020
Publication typeA1 Journal article-refereed


We present a general framework which can handle different processing stages of the three-dimensional (3D) scene representation referred to as 'view-plus-depth' (V+Z). The main component of the framework is the relation between the depth map and the super-pixel segmentation of the color image. We propose a hierarchical super-pixel segmentation which keeps the same boundaries between hierarchical segmentation layers. Such segmentation allows for a corresponding depth segmentation, decimation and reconstruction with varying quality and is instrumental in tasks such as depth compression and 3D data fusion. For the latter we utilize a cross-modality reconstruction filter which is adaptive to the size of the refining super-pixel segments. We propose a novel depth encoding scheme, which includes specific arithmetic encoder and handles misalignment outliers. We demonstrate that our scheme is especially applicable for low bit-rate depth encoding and for fusing color and depth data, where the latter is noisy and with lower spatial resolution.


  • 3-D depth, 3D, compression, fusion, super-pixel, time-of-flight, ToF, V+D, V+Z, view-plus-depth

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