Reflectance Transformation Imaging (RTI) System for Ancient Documentary Artefacts

This tutorial summarises our uses of reflectance transformation imaging in archaeological contexts. It introduces the UK AHRC funded project reflectance Transformation Imaging for Anciant Documentary Artefacts and demonstrates imaging methodologies

Testing QoE in Different 3D HDTV Technologies

The three dimensional (3D) display technology has started flooding the consumer television market. There is a number of different systems available with different marketing strategies and different advertised advantages. The main goal of the experiment described in this paper is to compare the systems in terms of achievable Quality of Experience (QoE) in different situations. The display systems considered are the liquid crystal display using polarized light and passive lightweight glasses for the separation of the left- and right-eye images, a plasma display with time multiplexed images and active shutter glasses and a projection system with time multiplexed images and active shutter glasses. As no standardized test methodology has been defined for testing of stereoscopic systems, we develop our own approach to testing different aspects of QoE on different systems without reference using semantic differential scales. We present an analysis of scores with respect to different phenomena under study and define which of the tested aspects can really express a difference in the performance of the considered display technologies

Evaluation of the damages caused by seismic events: First tests on supporting traditional multispectral classification with DSM

Seismic damages, as a roof entirely collapsed on the ground, are very difficult to be found using only multispectral classification algorithms. The availability of high resolution stereopairs from satellite disclose new possible fields of application to estimate changes and transformations of areas following catastrophic events. Combining both techniques it is obviously possible only when stereoscopic and multispectral images are available. In this case, as for all monitoring studies, it is necessary to compare the present situation to the pre-seismic one. The pre-seismic situation can be advantageously studied by classic photogrammetric techniques based on aerial frames, that are available in archives managed by photogrammetric companies and local government agencies. But it is also possible to extract the pre-seismic morphology from digital maps, containing the three-dimensional characteristics of the buildings. The present research tries to: a) improve the digital surface model extracted from Ikonos satellite images covering an area of central Italy (Foligno, Umbria), through a pre-treatment of images and a manual editing b) study the best DSM models to improve the detection of height difference, mainly in urban areas, and evaluate the results of the classification of land cover as further data to detect changes in building shape. DSM obtained by three-dimensional maps have been compared with DSM extracted directly from aerial stereo-pairs using different approaches. In the area under study a seismic event happened in September of the '97 causing relevant damages to different urbanized centres of the area

Methods for reducing visual discomfort in stereoscopic 3D: A review

This work was supported by the EPSRC Grant EP/M01469X/1, “Geometric Evaluation of Stereoscopic Video”

Stereoscopic visual saliency prediction based on stereo contrast and stereo focus

© 2017, The Author(s). In this paper, we exploit two characteristics of stereoscopic vision: the pop-out effect and the comfort zone. We propose a visual saliency prediction model for stereoscopic images based on stereo contrast and stereo focus models. The stereo contrast model measures stereo saliency based on the color/depth contrast and the pop-out effect. The stereo focus model describes the degree of focus based on monocular focus and the comfort zone. After obtaining the values of the stereo contrast and stereo focus models in parallel, an enhancement based on clustering is performed on both values. We then apply a multi-scale fusion to form the respective maps of the two models. Last, we use a Bayesian integration scheme to integrate the two maps (the stereo contrast and stereo focus maps) into the stereo saliency map. Experimental results on two eye-tracking databases show that our proposed method outperforms the state-of-the-art saliency models