Layered object detection for multi-class segmentation

We formulate a layered model for object detection and multi-class segmentation. Our system uses the output of a bank of object detectors in order to define shape priors for support masks and then estimates appearance, depth ordering and labeling of pixels in the image. We train our system on the PAS...

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Veröffentlicht in:2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition S. 3113 - 3120
Hauptverfasser: Yi Yang, Hallman, S, Ramanan, D, Fowlkes, C
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.06.2010
Schlagworte:
Benchmark testing
Computer science
Detectors
Humans
Image segmentation
Labeling
Object detection
Pixel
Shape
System testing
ISBN:1424469848, 9781424469840
ISSN:1063-6919, 1063-6919
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:We formulate a layered model for object detection and multi-class segmentation. Our system uses the output of a bank of object detectors in order to define shape priors for support masks and then estimates appearance, depth ordering and labeling of pixels in the image. We train our system on the PASCAL segmentation challenge dataset and show good test results with state of the art performance in several categories including segmenting humans.
ISBN:1424469848
9781424469840
ISSN:1063-6919
1063-6919
DOI:10.1109/CVPR.2010.5540070