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ECCV
2006
Springer

Object Detection by Contour Segment Networks

15 years 26 days ago
Object Detection by Contour Segment Networks
We propose a method for object detection in cluttered real images, given a single hand-drawn example as model. The image edges are partitioned into contour segments and organized in an image representation which encodes their interconnections: the Contour Segment Network. The object detection problem is formulated as finding paths through the network resembling the model outlines, and a computationally efficient detection technique is presented. An extensive experimental evaluation on detecting five diverse object classes over hundreds of images demonstrates that our method works in very cluttered images, allows for scale changes and considerable intra-class shape variation, is robust to interrupted contours, and is computationally efficient.
Vittorio Ferrari, Tinne Tuytelaars, Luc J. Van Goo
Added 16 Oct 2009
Updated 16 Oct 2009
Type Conference
Year 2006
Where ECCV
Authors Vittorio Ferrari, Tinne Tuytelaars, Luc J. Van Gool
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