Paper
22 June 1994 Dynamic integration of depth maps
Francesco P. Lovergine, Ettore Stella, Arcangelo Distante
Author Affiliations +
Abstract
This paper deals with a data fusion technique for depth reconstruction which integrates regularization by variational methods with stochastic optimization based on Kalman filtering. A framework for the fusion of multiple regularized depth maps is proposed for on-line integration of many views of the visible scene. This kind of approach has some advantages in respect with similar ones, as it is stressed widely in the paper. It does not use optical flow, camera modeling or an explicit motion equation and can be used to fuse stochastically both sparse or dense depth data, obtaining reliable estimates in the whole image domain.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Francesco P. Lovergine, Ettore Stella, and Arcangelo Distante "Dynamic integration of depth maps", Proc. SPIE 2233, Sensor Fusion and Aerospace Applications II, (22 June 1994); https://doi.org/10.1117/12.179047
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KEYWORDS
Filtering (signal processing)

Motion models

3D modeling

Data modeling

Stochastic processes

Cameras

Error analysis

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