Steganalysis of 3D objects using statistics of local feature sets

3D steganalysis aims to identify subtle invisible changes produced in graphical objects through digital watermarking or steganography. Sets of statistical representations of 3D features, extracted from both cover and stego 3D mesh objects, are used as inputs into machine learning classifiers in order to decide whether any information was hidden in the given graphical object. The features proposed in this paper include those representing the local object curvature, vertex normals, the local geometry representation in the spherical coordinate system. The effectiveness of these features is tested in various combinations with other features used for 3D steganalysis. The relevance of each feature for 3D steganalysis is assessed using the Pearson correlation coefficient. Six different 3D watermarking and steganographic methods are used for creating the stego-objects used in the evaluation study

Surface curvature maps and Michelangelo’s David

In 1998- 1999 a team of researchers from the Computer Science Departments at the University of Stanford and the University of Washington digitized a number of Michelangelo’s sculptures, including the David statue, using a custom designed laser triangulation scanner. The resultant data has been made available to the research community. This paper explores the data structures and the inherent geometry associated with the David data set. An estimation of surface curvature that exploits the structure and geometry of the data set is described. Finally surface curvature maps are defined and several curvature maps of David are presented

NeSI capability development for researchers: Providing a supported framework for learning

NeSI’s vision for its Capability Development Programme is to make available to NZ researchers appropriate training to take advantage of NeSI’s high performance computing (HPC) systems and other eResearch technologies. The overarching theme of the programme is to enable researchers to accelerate their research outcomes with the objective to empower researchers to make the most effective use of the NeSI platforms. Our presentation outlines this programme’s main areas of focus for 2015 and provides some highlights on a few key activities

Simulation of Calcium Dynamics in Realistic Three-Dimensional Domains

The cytosolic concentration of free calcium ions ([Ca2+]) is an important intracellular messenger in most cell types, and the spatial distribution of [Ca2+] is often critical. In a salivary gland acinar cell, a polarised epithelial cell, whose principal function is to transport water and thus secrete saliva, [Ca2+] controls the secretion of primary saliva, but increases in [Ca2+] are localised to the apical regions of the cell. Hence, any quantitative explanation of how [Ca2+] controls saliva secretion must take into careful account the spatial distribution of the various Ca2+ sources, Ca2+ sinks, and Ca2+-sensitive ion channels. Based on optical slices, we have previously constructed anatomically accurate three-dimensional models of seven salivary gland acinar cells, and thus shown that a model in which Ca2+ responses are confined to the apical regions of the cell is sufficient to provide a quantitative and predictive explanation of primary saliva secretion. However, reconstruction of such anatomically accurate cells is extremely time consuming and inefficient. Here, we present an alternative, mostly automated method of constructing three-dimensional cells that are approximately anatomically accurate and show that the new construction preserves the quantitative accuracy of the model