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A Local Histogram Based Descriptor for Object Tracking in Wide Area Motion Imagery

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CONTRIBUTORS:
  Author Alex Mathew
  Author Vijayan K. Asari
JOURNAL:
  International Journal of Information Processing, 6(4), 1 - 12.
YEAR: 2012
PUB TYPE: Journal Article
SUBJECT(S): Aerial Images, CLIF Data, Low Resolution Object Detection, Tracking, Wide Area Surveillance.
DISCIPLINE: Computer Science
HTTP: http://www.ijipbangalore.org
LANGUAGE: English
PUB ID: 103-511-681 (Last edited on 2013/01/16 22:54:42 US/Mountain)
SPONSOR(S):
 
ABSTRACT:
In this paper we propose a novel feature extraction technique and show its application in tracking in low resolution videos. The aspects that make tracking particularly challenging are global camera motion, large target movement, poor gradient and texture information and absence of color information. Global camera motion is reduced or eliminated by registering the images from frame to frame employing SURF (Speeded Up Robust Feature). The proposed method is based on intensity histogram, but with a variant that encodes both spatial and intensity information. The method is evaluated on CLIF (Columbus Large Image Format) data. The robustness of the feature eliminates the need for background subtraction in videos. A performance comparison of our approach with other object descriptors such as HOG (Histogram of Gradients), SURF and SIFT (Scale Invariant Feature Transform) shows the effectiveness of the proposed descriptor
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