Camera Localization in Distributed Networks Using Trajectory Estimation

Table 1

Summary of the state-of-the-art approaches for sensor localization.

Classes	Approaches	References
Fine-grained localization	Maximum likelihood, trigonometric,	[13, 14, 30],
	Received signal strength, time difference of arrival	[9, 11]
Coarse-grained; (nonstatistical localization)	Multidimensional scaling	[16–19]
	Moving scene features	[20]
	Active badge location	[12]
Coarse-grained; (statistical localization)	Linear regression and Kalman filter	[31]
	Maximum a posterior probability estimation	[21, 27, 32]
	Simultaneous localization and mapping	[25, 26]
	Structure from motion	[22–24]
	Tracking and camera field of view information	[28]
	Vanishing points and known position	[29]