Authors:
Mathieu Laroze
;
Luc Courtrai
and
Sébastien Lefèvre
Affiliation:
Univ. Bretagne-Sud, France
Keyword(s):
Human Detection, Image Stitching, Aerial Imagery, Image Mosaicing, Patch Classification, Object Detection.
Related
Ontology
Subjects/Areas/Topics:
Applications and Services
;
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Image Registration
;
Mobile Imaging
;
Shape Representation and Matching
Abstract:
Automatic human identification from aerial image time series or video sequences is a challenging issue. We
propose here a complete processing chain that operates in the context of recreational shellfish gatherers counting
in a coastal environment (the Gulf of Morbihan, South Brittany, France). It starts from a series of aerial
photographs and builds a mosaic in order to prevent multiple occurrences of the same objects on the overlapping
parts of aerial images. To do so, several stitching techniques are reviewed and discussed in the context of
large aerial scenes. Then people detection is addressed through a sliding window analysis combining the HOG
descriptor and a supervised classifier. Several classification methods are compared, including SVM, Random
Forests, and AdaBoost. Experimental results show the interest of the proposed approach, and provides directions
for future research.