SHOT: Scenario-Type Hypothesis Object Tracking with Indoor Sensor Networks

Abstract

SUMMARYIn the present paper, we propose an object tracking method called scenario-type hypothesis object tracking. In the proposed method, an indoor monitoring region is divided into multiple closed microcells using sensor nodes that can detect objects and their moving directions. Sensor information is accumulated in a tracking server through wireless multihop networks, and object tracking is performed at the tracking server. In order to estimate the trajectory of objects from sensor information, we introduce a novel concept of the virtual world, which consists of virtual micro-cells and virtual objects. Virtual objects are generated, transferred, and deleted in virtual micro-cells according to sensor information. In order to handle specific movements of objects in micro-cells, such as slowdown of passing objects in a narrow passageway, we also consider the generation of virtual objects according to interactions among virtual objects. In addition, virtual objects are generated when the tracking server estimates loss of sensor information in order to decrease the number of object tracking failures. Through simulations, we confirm that the ratio of successful tracking is improved by up to 29% by considering interactions among virtual objects. Furthermore, the tracking performance is improved up to 6% by considering loss of sensor information.

Tracking Pedestrians across Multiple Microcells Based on Successive Bayesian Estimations

“…We assume that each gate can detect pedestrian arrival or departure events with the pedestrians' moving directions using a pair of binary sensors [7–11]. Our system focuses on pedestrian tracking in a building, where multiple pedestrians move.…”

“…In this paper, we consider a pedestrian tracking system where sensor nodes are placed only at gates so that the monitoring region is divided into multiple smaller regions referred to as microcells, as shown in Figure 1 . We assume that each gate can detect pedestrian arrival or departure events with the pedestrians' moving directions using a pair of binary sensors [ 7 – 11 ]. Our system focuses on pedestrian tracking in a building, where multiple pedestrians move.…”