Boosting Image Orientation Detection with Indoor vs. Outdoor Classification

Authors:
Lei Zhang;Mingjing Li;Hong-Jiang Zhang
Affiliations:
-;-;-
Venue:
WACV '02 Proceedings of the Sixth IEEE Workshop on Applications of Computer Vision
Year:
2002

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Abstract

Automatic detection of image orientation is a veryimportant operation in photo image management. In thispaper, we propose an automated method based on theboosting algorithm to estimate image orientations. Theproposed method has the capability of rejecting imagesbased on the confidence score of the orientation detection.Also, images are classified into indoor and outdoor, andthis classification result is used to further refine theorientation detection. To select features more sensitive tothe rotation, we combine the features by subtractionoperation and select the most useful features by boostingalgorithm. The proposed method has several advantages:small model size, fast classification speed, and effectiverejection scheme.