Observer Localization using ConvNets
نویسنده
چکیده
Tracking and retrieving the exact location of an object in a 3D environment is major challenge in many situations such as navigation and orientation inside an indoor environment. Current radio based localization techniques such as Global Positioning Systems (GPS) and cellular network data are limited by their accuracies due to relatively large wavelength of radio signals compared to accuracies required in many of these scenarios. In this project we explore the possibility of detecting the location of an object in a scene, or alternately, the location of the observer based on visual data. Visual data is indeed the default way humans orient themselves in an indoor environment is by visual data. In addition we propose to use 3D models of real objects to obtain training data. Below is a few examples where such an approach to localization can be applied:
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