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Food Classifier using neural networks- this implem
2.0
Foodcam Classifier
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A Bag Of Visual Words classifier for MIT Media Lab's Foodcam.
Built using OpenCV 2.3
Implementing BOVW method: Visual Categorization with Bags of Keypoints by Gabriella Csurka, Christopher R. Dance, Lixin Fan, Jutta Willamowski, Cedric Bray, 2004.
Using Opponent-Color SURF features (192 floats): Van de Sande et al., CGIV 2008 Color Descriptors for Object Category Recognition. (they used SIFT)
Radial Basis Function SVMs for classification.
This is basically a primer to BOVW methods using OpenCV, which are dead simple.
I tweaked the basic method by:
- using background subtraction (since these are pictures from a still camera).
- using a sliding window. This enables better multi-class decisions, and actually paves the path to image segmentation.
Compiling
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Basically, just run:
majid0001 0 0
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It consists on how to identify 3 shapes (rectangle
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A very simple program that trains a neural network
with 9 images(3 rectangles, 3 triangles and 3 circles)and then simulates
the neural network in way to recognize 3 others images(1 rectangles, 1
triangles and 1 circles).
majid0001 2 0
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