Dense pixel matching between unrectified and distorted images using dynamic programming

In this paper, a novel framework for dense pixel matching based on dynamic programming is introduced. Unlike most techniques proposed in the literature, our approach assumes neither known camera geometry nor the availability of rectified images. Under such conditions, the matching task cannot be reduced to finding correspondences between a pair of scanlines. We propose to extend existing dynamic programming methodologies to a larger dimensional space by using a 3D scoring matrix so that correspondences between a line and a whole image can be calculated. After assessing our framework on a standard evaluation dataset of rectified stereo images, experiments are conducted on unrectified and non-linearly distorted images. Results validate our new approach and reveal the versatility of our algorithm.

An optimized stereo vision implementation for embedded systems: application to RGB and Infra-Red images

The aim of this paper is to demonstrate the applicability and the effectiveness of a computationally demanding stereo matching algorithm in different lowcost and low-complexity embedded devices, by focusing on the analysis of timing and image quality performances. Various optimizations have been implemented to allow its deployment on specific hardware architectures while decreasing memory and processing time requirements: (1) reduction of color channel information and resolution for input images, (2) low-level software optimizations such as parallel computation, replacement of function calls or loop unrolling, (3) reduction of redundant data structures and internal data representation. The feasibility of a stereovision system on a low cost platform is evaluated by using standard datasets and images taken from Infra-Red (IR) cameras. Analysis of the resulting disparity map accuracy with respect to a full-size dataset is performed as well as the testing of suboptimal solutions

Bioinformatics inspired algorithm for stereo correspondence

In this paper, we exploit the analogy between protein sequence alignment and image pair correspondence to design a bioinformatics-inspired framework for stereo matching based on dynamic programming. This approach also led to the creation of a meaningfulness graph, which helps to predict matching validity according to image overlap and pixel similarity. Finally, we propose an automatic procedure to estimate automatically all matching parameters. This work is evaluated qualitatively and quantitatively using a standard benchmarking dataset and by conducting stereo matching experiments between images captured at different resolutions. Results confirm the validity of the computer vision/bioinformatics analogy to develop a versatile and accurate low complexity stereo matching algorithm.

The Violent Maintenance of the Portuguese Colonial Identity and the Search for a Postcolonial one: literary images of Portugal as a colonial and postcolonial nation

Through the examination of Camões's Os Lusíadas , Sena's Os Grão-Capitães and Saramago's A Jangada de Pedra , this article explores violence as a means of shaping Portuguese identity in different historical contexts, and how these works portray the continued recourse to violence as Portugal moves from colonizing to postcolonial nation.

Making Risk Visible. The role of images in the assessment of (cancer) genetic risk

Whilst analysis of 'risk' (in its many conceptual shapes) has loomed large in both medicine and social sciences over the past 25 years, detailed investigations as to how risk assessments are actually put together (in either lay or professional contexts) are few in number. The studies that are available usually focus on the use of words or everyday conversation in assembling risk. Talking about risk is, of course, important, but what tends to be ignored is the fact that risk can be and is often made visible. For example, it can be made visible through the use of tables, charts, diagrams and various kinds of sophisticated laboratory images. This paper concentrates on the role of such images in the context of a cancer genetics clinic and its associated laboratory. Precisely how these images are tied into the production of risk estimates, how professionals discuss and use such images in clinical work, and how professionals reference them to display facts about risk is the focus of the paper. The paper concludes by highlighting the significance of different kinds of visibility for an understanding of genetic abnormalities and how such differences might impact on the attempts of lay people to get to grips with risk.

SrTiO3(001)(2x1) reconstructions: First-principles calculations of surface energy and atomic structure compared with scanning tunneling microscopy images

(1x1) and (2x1) reconstructions of the (001) SrTiO3 surface were studied using the first-principles full-potential linear muffin-tin orbital method. Surface energies were calculated as a function of TiO2 chemical potential, oxygen partial pressure and temperature. The (1x1) unreconstructed surfaces were found to be energetically stable for many of the conditions considered. Under conditions of very low oxygen partial pressure the (2x1) Ti2O3 reconstruction [Martin R. Castell, Surf. Sci. 505, 1 (2002)] is stable. The question as to why STM images of the (1x1) surfaces have not been obtained was addressed by calculating charge densities for each surface. These suggest that the (2x1) reconstructions would be easier to image than the (1x1) surfaces. The possibility that the presence of oxygen vacancies would destabilise the (1x1) surfaces was also investigated. If the (1x1) surfaces are unstable then there exists the further possibility that the (2x1) DL-TiO2 reconstruction [Natasha Erdman Nature (London) 419, 55 (2002)] is stable in a TiO2-rich environment and for p(O2)>10(-18) atm.