Localization related videos and short discussion.

There are three video links on this page. All of them show results of our particle filtering localization techniques. The first two demonstrate infrastructure based localization (a related paper can be found here), where the mobile node to be localized is talking to fixed access points (in our case, a single fixed access point). The third video demonstrates ad hoc localization (a related paper can be found here) where nodes in an ad hoc (or sensor) network can localize themselves based on location estimated from other nodes in the network.

	Video 1: the first video shows an outline of a small 1600 sqft (~150m2) house with a single access point located in the left center room. The mobile user is depicted with green circle. The belief of the system about the user's location is represented by the small red dots, i.e., the more (and the better) the red dots are concentrated on the green circle, the better the system's belief and estimate is. The video shows a real-life walkthrough.
	Video 2: the second video shows a similar situation to the first video. However, here the filter's system model is a perfect model of the user's movement profile. Such matching could be achieved by an inertial navigation system on the tracked device. The video clearly demonstrates the advantage of such approach.
	Video 3: the third video shows an ad hoc localization scenario, where we are showing the tracking of the green node. The nodes in the four corners represented by triangles are anchors (i.e., they have precise location information). The dashed circle around the tracked node represents its average transmission radius. The large black disc represents the mode of the particle filter, i.e., the system's estimate on the green node.