In this paper, we propose Li-Tect, an algorithm to detect the shape of an object located in an indoor environment using low cost optical elements through sensing the environment's light. The algorithm analyzes, relying on the predictability of optical propagation paths, how much light is expected to propagate in the absence of obstructions caused by the presence of an object. Then, based on the received light when the object is in the room, the algorithm infers the shape of the object. In addition, the algorithm considers the reflected paths from surfaces in order to determine the object's estimated shape. We study five different scenarios characterized by different levels of complexity, room sizes, and a range of reflection nodes. The algorithm is also tested in a real prototype where several experiments are carried out in two scenarios to demonstrate the capabilities of Li-Tect in 2-D and 3-D monitoring and shape detection cases. Finally, the results show that the shape and the detection of objects in the scenarios can be easily acquired with high accuracy, even if the number of transceivers is reduced.
Li-Tect: 3-D Monitoring and Shape Detection Using Visible Light Sensors / Alizadeh Jarchlo, E.; Tang, X.; Doroud, H.; Jimenez, V. P. G.; Lin, B.; Casari, P.; Ghassemlooy, Z.. - In: IEEE SENSORS JOURNAL. - ISSN 1530-437X. - 2019, 19:3(2019), pp. 940-949. [10.1109/JSEN.2018.2879398]
Li-Tect: 3-D Monitoring and Shape Detection Using Visible Light Sensors
Casari P.;
2019-01-01
Abstract
In this paper, we propose Li-Tect, an algorithm to detect the shape of an object located in an indoor environment using low cost optical elements through sensing the environment's light. The algorithm analyzes, relying on the predictability of optical propagation paths, how much light is expected to propagate in the absence of obstructions caused by the presence of an object. Then, based on the received light when the object is in the room, the algorithm infers the shape of the object. In addition, the algorithm considers the reflected paths from surfaces in order to determine the object's estimated shape. We study five different scenarios characterized by different levels of complexity, room sizes, and a range of reflection nodes. The algorithm is also tested in a real prototype where several experiments are carried out in two scenarios to demonstrate the capabilities of Li-Tect in 2-D and 3-D monitoring and shape detection cases. Finally, the results show that the shape and the detection of objects in the scenarios can be easily acquired with high accuracy, even if the number of transceivers is reduced.File | Dimensione | Formato | |
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