Indoor positioning with different technical solutions is omnipresent in industrial and academic research. The most important applications are Location Based Services (LBS), which objects require reference in a coordinate system. Research and development target for example the automation of processes in smart warehousing and logistics, or the monitoring of people during rescue missions. Indoor positioning is also highly relevant to robotics and autonomous navigation. The poor performance of Global Navigation Satellite Systems (GNSS) in indoor environments calls for other solutions. Diverse requirements and different environmental conditions, in particular Non-Line-of-Sight (NLoS) signal propagation, are reasons for the current insufficient level of performance in indoor positioning and navigation. Wireless devices (e.g. RFID systems) enjoy widespread use in numerous diverse applications including sensor networks, deployed in all environments and organizing themselves in an ad-hoc fashion. However, knowing the correct positions of network nodes and their deployment is an essential precondition. Optical sensors do not require the deployment of physical reference infrastructure inside buildings and offer several solutions covering all required accuracy levels.
In this project we intend to use stereo vision based indoor location whose applications lie in Location Based Services. Using fixed cameras, to detect a known object, and try to locate its position in space.We have implemented two approaches, the first approach which measures the number pixels occupied by the object on the picture and come up a mapping between the change of size in pixels and distance from camera. The second approach is to use stereo images to create a depth image of the scene, where the relative distances of the objects are color coded.
In this project we intend to use stereo vision based indoor location whose applications lie in Location Based Services. Using fixed cameras, to detect a known object, and try to locate its position in space.We have implemented two approaches, the first approach which measures the number pixels occupied by the object on the picture and come up a mapping between the change of size in pixels and distance from camera. The second approach is to use stereo images to create a depth image of the scene, where the relative distances of the objects are color coded.