1. A method of detecting an object of interest in a first image comprising: receiving the first image; performing run-length encoding on the first image to identify edges for a shape bounding a candidate object; generating a hypothesis that the candidate object is the object of interest; calculating a histogram of gradients for the candidate object; classifying the candidate object as the object of interest using a support vector machine method; computing a summed area table for a second image, the second image containing the candidate object of the first image, the candidate object having associated with it a shape bounding the candidate object; and dividing the shape into discrete regions and using the summed area table to test for symmetry between regions.