Abstract
Object localization is an important task in the visual surveillance of scenes, and it has important applications in locating personnel and/or equipment in large open spaces such as a farm or a mine. Traditionally, object localization can be performed using the technique of stereo vision: using two fixed cameras for a moving object, or using a single moving camera for a stationary object. This research addresses the problem of determining the location of a moving object using only a single moving camera, and it does not make use of any prior information on the type of object nor the size of the object. Our technique makes use of a single camera mounted on a quadrotor drone, which flies in a specific pattern relative to the object in order to remove the depth ambiguity associated with their relative motion. In our previous work, we showed that with three images, we can recover the location of an object moving parallel to the direction of motion of the camera. In this research, we find that with four images, we can recover the location of an object moving linearly in an arbitrary direction. We evaluated our algorithm on over 70 image sequences of objects moving in various directions, and the results showed a much smaller depth error rate (less than 8.0% typically) than other state-of-the-art algorithms.
Funder
National Research Foundation of Korea
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Cited by
6 articles.
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