Visual Hull-Based Geometric Data Compression of a 3-D Object
| Autor: | Sung Soo Hwang, Wook-Joong Kim, Seong-Dae Kim, Jisung Yoo |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
business.industry
Pattern recognition Object (computer science) Visual hull Silhouette Visualization Image (mathematics) Encoding (memory) Compression (functional analysis) Media Technology Computer vision Artificial intelligence Electrical and Electronic Engineering business Mathematics Geometric data analysis |
| Zdroj: | IEEE Transactions on Circuits and Systems for Video Technology. 25:1151-1160 |
| ISSN: | 1558-2205 1051-8215 |
| Popis: | As image-based 3-D modeling is used in a variety of applications, accordingly, the compression of 3-D object geometry represented by multiple images becomes an important task. This paper presents a model-based approach to predict the geometric structure of an object using its visual hull. A visual hull is a geometric entity generated by shape-from-silhouette (SFS), and consequently it largely follows the overall shape of the object. The construction of a visual hull is computationally inexpensive and a visual hull can be encoded with relatively small amount of bits because it can be represented with 2-D silhouette images. Therefore, when it comes to the predictive compression of object’s geometric data, the visual hull should be an effective predictor. In the proposed method, the geometric structure of an object is represented by a layered depth image (LDI), and a visual hull from the LDI data is computed via silhouette generation and SFS. The geometry of an object is predicted with the computed visual hull, and the visual hull data with its prediction errors are encoded. Simulation results show that the proposed predictive coding based on visual hull outperforms the previous image-based methods and the partial surface-based method. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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