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Energy efficient object detection an...

Yang, Jing.

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Energy efficient object detection and measurement for smart glasses.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Energy efficient object detection and measurement for smart glasses./
Author:	Yang, Jing.
Description:	47 p.
Notes:	Source: Masters Abstracts International, Volume: 52-06.
Contained By:	Masters Abstracts International52-06(E).
Subject:	Computer science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1555468
ISBN:	9781303879784

Energy efficient object detection and measurement for smart glasses.
Yang, Jing.

Energy efficient object detection and measurement for smart glasses. - 47 p.

Source: Masters Abstracts International, Volume: 52-06.

Thesis (M.S.)--Michigan State University, 2014.

This item must not be sold to any third party vendors.

We design and implement a novel object detection and measurement system called Lockon for smart glasses. Lockon takes the advantages of the mounting position of the smart glasses, and provides users two useful functions that can benefit a wide range of applications. Lockon can accurately locate the object of interest (OoI) in the view of the user and inform the user the position of the OoI in real-time, using the front-facing camera equipped on the smart glasses and advanced computer vision and image processing techniques. To conserve energy, Lockon implements a motion trigger to intelligently activate the object detection process only when it is necessary. Lockon can also accurately measure the dimension of the object, with a 3D ranging technique. This capability allows user to remotely estimate the dimension of the object. We implement Lockon on Google Glass Explorer Edition, and evaluate the performance of Lockon using extensive experiments. Our results indicate that Lockon can achieve high detection accuracy (0.95 true positive rate and 4.3 x 10 --7 false positive rate), low object dimension measurement error (3.3% when distance is less than 1 m), and low delay (300 ms).

ISBN: 9781303879784Subjects--Topical Terms:

523869
Computer science.

Energy efficient object detection and measurement for smart glasses.
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245 1 0 $a Energy efficient object detection and measurement for smart glasses.
300 $a 47 p.
500 $a Source: Masters Abstracts International, Volume: 52-06.
500 $a Adviser: Guoliang Xing.
502 $a Thesis (M.S.)--Michigan State University, 2014.
506 $a This item must not be sold to any third party vendors.
506 $a This item must not be added to any third party search indexes.
520 $a We design and implement a novel object detection and measurement system called Lockon for smart glasses. Lockon takes the advantages of the mounting position of the smart glasses, and provides users two useful functions that can benefit a wide range of applications. Lockon can accurately locate the object of interest (OoI) in the view of the user and inform the user the position of the OoI in real-time, using the front-facing camera equipped on the smart glasses and advanced computer vision and image processing techniques. To conserve energy, Lockon implements a motion trigger to intelligently activate the object detection process only when it is necessary. Lockon can also accurately measure the dimension of the object, with a 3D ranging technique. This capability allows user to remotely estimate the dimension of the object. We implement Lockon on Google Glass Explorer Edition, and evaluate the performance of Lockon using extensive experiments. Our results indicate that Lockon can achieve high detection accuracy (0.95 true positive rate and 4.3 x 10 --7 false positive rate), low object dimension measurement error (3.3% when distance is less than 1 m), and low delay (300 ms).
590 $a School code: 0128.
650 4 $a Computer science. $3 523869
650 4 $a Artificial intelligence. $3 516317
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690 $a 0800
710 2 0 $a Michigan State University. $b Computer Science. $3 1680297
773 0 $t Masters Abstracts International $g 52-06(E).
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791 $a M.S.
792 $a 2014
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1555468