Object Detection Using Am-Fm Features
This paper presents a template-based approach to detect objects of interest from real images. The authors rely on AM-FM models and specifically, on the Dominant Component Analysis (DCA) for feature extraction. They incorporate the results from AM-FM models for object detection. In order to detect the object of interest from real images patches are introduced. In order to find the degree of match between the patch and template, the AM-FM features are calculated. To find the correlation between the template and image patch, mean and standard deviation of image patch and template are calculated.