NDLI: Video Based Real-World Remote Target Tracking on Smartphones

Content Provider	IEEE Xplore Digital Library
Author	Qia Wang Lobzhanidze, A. Jang, H.I. Wenjun Zeng Yi Shang
Copyright Year	2012
Abstract	Smartphone's increasing computing power and built-in sensors such as digital camera and GPS have created a new and open platform for developing compelling mobile multimedia tools and systems. In this paper, a novel, accurate and computationally efficient video-based remote target positioning and tracking system on Android smart phones is proposed and presented, with the assumption that the physical size of the remote target is known. Smartphone's user-friendly interface is exploited in our system to facilitate accurate and efficient video object tracking. With the help of some initial user input, our algorithm generates tight bounding boxes around the moving targets across video frames with high accuracy and low complexity. Unlike most existing video tracking systems that are limited to tracking on the image plane, we re-project the accurately detected object locations on the image plane to real world positions to estimate the remote target's moving trajectory. In addition, the Extended Kalman Filtering model is applied to provide a smooth remote target trajectory and velocity estimation. Our experimental results show that the proposed mobile multimedia system works accurately and efficiently for tracking remote moving targets.
Starting Page	693
Ending Page	698
File Size	1979204
Page Count	6
File Format	PDF
ISBN	9781467316590
ISSN	19457871
DOI	10.1109/ICME.2012.188
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-09
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Smart phones Target tracking Estimation Trajectory Cameras Computer vision Extended Kalman filtering Mobile multimedia system Smartphones Video object tracking Remote target positioning and tracking
Content Type	Text
Resource Type	Article

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