Steganography through perspective invariance

Yaşaroğlu, Yağız
A novel approach for watermarking of 3D models is introduced, for which data is embedded into 3D models, whereas extracted from their projected 2D visual or 2D-plus-depth representations. Such a watermarking system is valuable, since most of the 3D content is being consumed as 2D visual data. Apart from the efficiency of embedding data into 3D models before generation of arbitrary 2D projections, in some use cases, such as free viewpoint video or computer games, 2D content has to be rendered at the client, where watermarking is less secure. In order to achieve this aim, 3D-2D perspective projection invariants, as well as 3D projective invariants are used and utilization of such invariants enables the method to be independent of the viewpoint from which 2D representations are generated. The first method proposed employs a perspective projection invariant to extract hidden data from an arbitrary 2D view of a watermarked 3D model. Data is encoded in the relative positions of six interest points, selection of which requires minimal criteria. Two main problems for such a watermarking system are identified as noise sensitivity of the invariant and repeatability of the interest point detection. By optimizing an objective function considering this sensitivity, the optimal 3D interest point displacements are obtained. Performance of the proposed system is evaluated through simulations on polygonal 3D mesh models and the results strongly indicate that perspective invariant-based watermarking is feasible. As an extenstion for 2D plus depth representation of 3D models, data embedded in 3D models is also detected by combining information in 2D views and range data by utilizing another projective invariant. Finally, the problem of repeatable interest point detection that remain detectable after data embedding, is also examined and a novel method to identify such repeatable interest points is presented. The proposed methods indicate a new direction in watermarking research.


Robust transmission of 3D models
Bici, Mehmet Oğuz; Akar, Gözde; Department of Electrical and Electronics Engineering (2010)
In this thesis, robust transmission of 3D models represented by static or time consistent animated meshes is studied from the aspects of scalable coding, multiple description coding (MDC) and error resilient coding. First, three methods for MDC of static meshes are proposed which are based on multiple description scalar quantization, partitioning wavelet trees and optimal protection of scalable bitstream by forward error correction (FEC) respectively. For each method, optimizations and tools to decrease com...
Extraction of 3D transform and scale invariant patches from range scans
Akagunduz, Erdern; Ulusoy, İlkay (2007-06-22)
An algorithm is proposed to extract transformation and scale invariant 3D fundamental elements from the surface structure of 3D range scan data. The surface is described by mean and Gaussian curvature values at every data point at various scales and a scale-space search is performed in order to extract the fundamental structures and to estimate the location and the scale of each fundamental structure. The extracted fundamental structures can later be used as nodes in a topological graph where the links betw...
Yasaroglu, Yagiz; Alatan, Abdullah Aydın (2014-10-30)
A novel watermarking method is presented in which the data embedded into a 3D model is extracted from an arbitrary 2D view by using a perspective projective invariant. The data is embedded into 3D positions of selected interest points on a 3D mesh. Determining the interest point modification vectors for ensuring watermark detection constitutes an important part of the proposed method. Different watermark embedding schemes based on optimization of the watermark function are implemented and evaluated. Another...
3D object recognition using scale space of curvatures
Akagündüz, Erdem; Ulusoy, İlkay; Department of Electrical and Electronics Engineering (2011)
In this thesis, a generic, scale and resolution invariant method to extract 3D features from 3D surfaces, is proposed. Features are extracted with their scale (metric size and resolution) from range images using scale-space of 3D surface curvatures. Different from previous scale-space approaches; connected components within the classified curvature scale-space are extracted as features. Furthermore, scales of features are extracted invariant of the metric size or the sampling of the range images. Geometric ...
3D object representation using transform and scale invariant 3D features
AKAGÜNDÜZ, Erdem; Ulusoy, İlkay (2007-10-21)
An algorithm is proposed for 3D object representation using generic 3D features which are transformation and scale invariant. Descriptive 3D features and their relations are used to construct a graphical model for the object which is later trained and then used for detection purposes. Descriptive 3D features are the fundamental structures which are extracted from the surface of the 3D scanner output. This surface is described by mean and Gaussian curvature values at every data point at various scales and a ...
Citation Formats
Y. Yaşaroğlu, “Steganography through perspective invariance,” Ph.D. - Doctoral Program, Middle East Technical University, 2012.