In this paper we proposed a method for geometric calibration of a projector. This method makes use of a calibrated camera to calibrate the projector. Since the projector works inversely with a camera i.e., it projects the image instead of capturing it, so it can be considered as a reverse camera. The projector is calibrated with the help of a calibrated camera using two types of chessboard, a printed chessboard and a projected chessboard by the projector. The object points of the projected chessboard pattern are measured with the help of calibrated camera and the image points are directly acquired from the chessboard pattern to be projected. Then using these object points and image points the projector is calibrated. Once the projector calibration is done, the transformation matrices (from projector to screen, from camera to screen and from camera to projector) are determined which are used for the reconstruction of the 3D geometry.
Sand models as used in military are thematic 3D representations of an area of interest which combined the information of maps with a more realistic 3D bird's eye view of the terrain. Sand models have been used for military planning and war gaming for many years as a field expedient, small-scale map, for planning and training of military operations. This, however increasingly fell out of favor with improved maps, aerial and satellite photography, and later, with digital terrain simulations. The proposed system, a Digital Sand Model (DSM) using a Virtual Reality (VR) Workbench, is a digital replica of the same. It involves a leader interacting with the digital environment and other viewers share his view of the digital scene. The system uses a stereoscopic projector, a mirror and Viewing Screen setup to produce a 3D stereoscopic display. This VR system allows performing interactive 3D explorations via stereo camera setup and wearable IR LEDs. A gesture recognition system is also described which allows interaction with the system. The proposed system uses Model-View-Controller (MVC) architecture as the software design.
Stereo vision is a low cost and passive mechanism to perceive the environment for robotic applications. The huge compute requirements of stereo vision algorithms have been a major challenge for their usage in real world applications on small robots. Standard stereo depth estimation algorithms Sum of Absolute Differences (SAD), census transform and an advanced algorithm Semi-Global Matching (SGM) are discussed in this work. This paper presents novel real time implementation of these three stereo vision algorithms on two different compute platforms i) Intel AVX (Advanced Vector Extension) and ii) Nvidia Jetson GPU (Graphical Processing Unit). The Intel CPU implementation of stereo algorithms is optimized by using OpenMP (Open Multi-Processing) for multi-threading, AVX registers for vectorization and several other novel ideas for real time processing. Nvidia Jetson implementation is efficiently designed for maximum speed-up on a low end GPU such as Jetson TK1. Post processing steps such as local extrema detection, left-right consistency and median filter are used to improve the final disparity image. We have achieved speedup of the order of 30x when compared with naïve CPU implementation.
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