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Brian P. Jackson

dblp:07/8116 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2010
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Image and video processing · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Image and video processing › image registration
aerial video registration
0.112010
Registering Aerial Video Images Using the Projective Constraint · IEEE Trans. Image Process. 2010
Image and video processing
image registration
0.112010
Registering Aerial Video Images Using the Projective Constraint · IEEE Trans. Image Process. 2010
Image and video processing › motion analysis
motion detection
0.112010
Registering Aerial Video Images Using the Projective Constraint · IEEE Trans. Image Process. 2010
Image and video processing › motion analysis
moving object detection
0.112010
Registering Aerial Video Images Using the Projective Constraint · IEEE Trans. Image Process. 2010

Methods — techniques the papers use, named apart from their topics

projective constraints · 0.1feature point matching · 0.1
YearPublicationVenuePosition
2010 Registering Aerial Video Images Using the Projective Constraint
abstract
To separate object motion from camera motion in an aerial video, consecutive frames are registered at their planar background. Feature points are selected in consecutive frames and those that belong to the background are identified using the projective constraint. Corresponding background feature points are then used to register and align the frames. By aligning video frames at the background and knowing that objects move against the background, a means to detect and track moving objects is provided. Only scenes with planar background are considered in this study. Experimental results show improvement in registration accuracy when using the projective constraint to determine the registration parameters as opposed to finding the registration parameters without the projective constraint.
Brian P. Jackson, A. Ardeshir Goshtasby
IEEE Trans. Image Process.1