1. A method for detecting an object in an image comprising: calculating, using a processor, a log L likelihood of pairs of pixels at select positions in the image, said select positions being derived from a plurality of first training images and a plurality of second training images; comparing, using a processor, said calculated log L likelihood of said pairs of pixels with a threshold value; and determining, using a processor, that the object has been detected when said calculated log L likelihood is greater than said threshold value; wherein said deriving of said select positions in the image includes, calculating pair-wise conditional distributions corresponding to the plurality of said first training images having a predetermined dimension and sample objects and said plurality of second training images having said predetermined dimension and sample non-objects; calculating conditional relative entropy values between all pairs of pixels in said first and second training images based on said pair-wise conditional distributions; and selecting a plurality of the largest conditional relative entropy values and corresponding pairs of pixels from said conditional relative entropy values calculated for said all pairs of pixels; and wherein said select positions correspond to said selected pairs of pixels from said conditional relative entropy values calculated for said all pairs of pixels.