Pivot-Object Motion Detection using Outcode - Nonatree
Pallavi Upadhyay, D K Sharma and Mukesh Upadhyay. Article: Pivot-Object Motion Detection using Outcode - Nonatree. IJCA Special Issue on Electronics, Information and Communication Engineering ICEICE(5):5-7, December 2011. Full text available. BibTeX
@article{key:article,
author = {Pallavi Upadhyay and D K Sharma and Mukesh Upadhyay},
title = {Article: Pivot-Object Motion Detection using Outcode - Nonatree},
journal = {IJCA Special Issue on Electronics, Information and Communication Engineering},
year = {2011},
volume = {ICEICE},
number = {5},
pages = {5-7},
month = {December},
note = {Full text available}
}
Abstract
Motion gaming and hand or body gestured controlled systems (Augmented Reality) is the future ahead, where the movement of hands or movement of pivot-object is used for exerting the controls, eliminating the need of joysticks and control pads.
In this paper we propose Outcode-Nonatree (OCNT), as a new methodology of identifying the motion of pivot-object in vicinity of camera. A live image of pivot-object is captured via camera; it is divided into 9 partitions (Nona-tree Partitions), labeled, using outcode. Then, recursively these partitions are scanned for appearance of pivot-object, till the partitioning fits approximately to the object size. This partition then defines the current position of the pivot-object, used to take the motion decisions.
The proposed methodology is applied for learning, memorizing and then identifying the position of the pivot-object.
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