A dense stereo reconstruction technique for extracting a 3D model of a rock scene from a pair of images is presented. The technique falls under the conventional approach of extracting 3D information from a calibrated stereo pair. In this work, a single camera that is under going linear motion with respect to the scene is used. As far as correspondence analysis is concerned, a simple method for ...

Model calculations for the photon-dominated region S 140 are presented. The overall geometry and an inhomogeneous density distribution are incorporated and the chemical and thermal balance is solved in two and three dimensions. The observed widespread neutral carbon emission in the extended molecular cloud is investigated for a range in clump size and volume filling factor. It is found that the...

This paper addresses the problem of environment representation for Simultaneous Localisation and Mapping (SLAM) algorithms. One of the main problems of SLAM is how to interpret and synthesize the external sensory information into a representation of the environment that can be used by the mobile robot to operate autonomously. Traditionally, SLAM algorithms have relied on sparse environment repr...

the growing population and increasing socio-economic necessitiescreates a pressure on land use/land cover. nowadays, land use change detection using remote sensing data provides quantitative and timely information for management and evaluation of natural resources. this study investigates the land use changes in part of hableh rood watershed of iran using landsat 7 and 8 (sensor etm+ and oli) i...

AbstructThis article presents a technique for registration and segmentation of dense depth maps provided by a stereo vision system. The vision system uses inertial sensors to give a reference for camera pose. The maps are registered dsing a modified version of the ICP Iterative Closest Point algorithm to register dense depth maps obtained from a stereo vision system. The proposed technique expl...

A mode-based clustering method is developed for identifying spatially dense clusters in brain maps. This type of clustering focuses on identifying clusters in brain maps independent of their shape or overall variance. This can be useful for both localization in terms of interpretation and for subsequent graphical analysis that might require more coherent or dense regions of interest as starting...