Abstract
This paper proposes methods for measuring size and distance of target objects by using mobile devices. For close-range measurement of a size of an object, users must hold the device close to the object and drag it along a desired direction. We develop a new approach for estimating a dragging distance of the device using acceleration signals retrieved from a three-axis accelerometer embedded on it. In the cases that target objects locate far from the device, users have to drag it vertically and two images of the objects are captured at starting and ending points of a dragging period. Then, the device displacement is estimated using acceleration signals, and a disparity of the object in two images is also determined via a matching technique based on Speeded Up Robust Features (SURF). The object disparity, dragging distance and device orientation are used as features to determine a distance between the target object and the device and also a size of it using learning-based scheme. Experimental results are presented to demonstrate a performance of the proposed methods.
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