| Summary: | 碩士 === 元智大學 === 資訊工程學系 === 99 === This thesis presents a progressive sharing method for protecting secret 3D Models. The proposed n-level (n >= 2) progressive 3D model sharing method divides the points of a 3D model in n groups, and encodes them in n+1 shadow models. Each shadow model has noisy appearance, and knowledge of a single shadow model gets nothing about the secret 3D model. A mimicked 3D model can be revealed when q ( 2 <= q <= n+1 ) shadow models are available, in which the quality of the revealed model is proportional to the number of shadow models engaged in the decoding process. The original 3D secret model can be revealed without any loss when all of the n+1 shadow models are obtained. The proposed sharing method manipulates 3D points represented in real numbers. We design the sharing function to work directly on real numbers represented in IEEE−754 standard floating point representation, which is novel in the field of sharing technology. In the proposed n-level progressive 3D model sharing method, a secret 3D model is encoded in n?1 shadow models. Each shadow model occupies smaller space and can be stored in separated storage. The small-size of each shadow model benefits the further processing such as transmission or storage. Besides, a mimicked model can be reconstructed even when some of the shadow models were crashed or lost, that increases the robustness to the secret 3D model. The point grouping algorithm designed in this study classifies the points of the secret 3D model evenly in spatial distribution, which enables the ability of progressive revealing to the secret model without depending on the order about the points stored in the original secret 3D model.
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