Participatory approaches elicit information from multiple stakeholders while planning and implementing resource management systems. Such elicited information is often associated with significant variability. Public participation geographical information science (GIS) (PP-GIS) solutions can reduce this variability by helping stakeholders to measure the factors involved and provide the elicited information. We propose a ‘Quality Function Deployment’-based participatory framework for developing such PP-GIS solutions. It is demonstrated using a case study to enhance an existing PP-GIS into a solution for rainwater harvesting systems in Indian villages. The novelty of the proposed framework is that it identifies metrics and carries out comparative analysis of three existing solutions: participatory rural appraisal, participatory mapping and PP-GIS. In the case study, PP-GIS scored less than participatory mapping as it scored less on usability and affordability. To improve PP-GIS in these aspects, an easy-to-use mobile and web based, free and open source PP-GIS solution, Watershed GIS, was developed. It scored better than the three existing solutions and its usage resulted in substantial reduction of variability in criteria values and thus better ranking of alternatives, with the average coefficient of variation decreasing from 0.12 to 0.05.

The problem of motion recovery for a head-eye system from stereo image sequences is addressed. Two types of motions, the translation of the vehicle and the panning motion of the head, are considered. It is shown how these motions and the depth map can be estimated directly from the measurements of image gradients and time derivatives. There is no need to estimate image motion, track a scene feature over time, or establish point correspondences in a stereo image pair. The results of various experiments with real scenes are presented.>

Practical lamps for undersea illumination are closely approximated by point sources, the light from which diverges and also attenuates due to scattering and absorption by the water. The objective is to determine the error introduced by these departures from the usual lighting assumptions of photometric stereo and to find an approach to solution of the brightness equations. It is demonstrated that an iterative approach to photometric stereo, plus a sparse range map containing as little as one range datum for each object in the scene, is sufficient to permit determination of the surface gradients. Simulation indicated that the method improves accuracy and was robust with respect to measurement error in both sparse range data and attenuation length.>