Real-time Computation of Haar-like features at generic angles for detection algorithms

This paper proposes a new approach to detect rotated objects at distinct angles using the Viola-Jones detector. The use of additional Integral Images makes an approximation the Haar-like features for any given angle. The proposed approach uses different types of Haar-like features, including features that compute areas at 45o, 26.5o and 63.5o of rotation. Given a trained classifier (using normal features) a conversion is made using a pair of features so an equivalent value is computed for any angle. This conversion is only an approximation, but the errors are constrained and they would have limited impact on the final accuracy of the classifier. We discuss the sources of errors in the computation of the Haar-like features and show through experiments that in natural images the errors are often negligible.