NDLI: Scale-invariant contour completion using conditional random fields

Content Provider	IEEE Xplore Digital Library
Author	Xiaofeng Ren Fowlkes, C.C. Malik, J.
Copyright Year	2005
Description	Author affiliation: Div. of Comput. Sci., California Univ., Berkeley, CA (Xiaofeng Ren; Fowlkes, C.C.; Malik, J.)
Abstract	We present a model of curvilinear grouping using piece-wise linear representations of contours and a conditional random field to capture continuity and the frequency of different junction types. Potential completions are generated by building a constrained Delaunay triangulation (CDT) over the set of contours found by a local edge detector. Maximum likelihood parameters for the model are learned from human labeled ground truth. Using held out test data, we measure how the model, by incorporating continuity structure, improves boundary detection over the local edge detector. We also compare performance with a baseline local classifier that operates on pairs of edgels. Both algorithms consistently dominate the low-level boundary detector at all thresholds. To our knowledge, this is the first time that curvilinear continuity has been shown quantitatively useful for a large variety of natural images. Better boundary detection has immediate application in the problem of object detection and recognition
Sponsorship	IEEE Comput. Soc. Tech. Comm. on Pattern Anal. and Machine Intelligence
Starting Page	1214
Ending Page	1221
File Size	721317
Page Count	8
File Format	PDF
ISBN	076952334X
ISSN	15505499
DOI	10.1109/ICCV.2005.213
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image edge detection Object detection Detectors Piecewise linear techniques Humans Layout Computer vision Face detection Image segmentation Computer science
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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