Local invariant algorithms are usually not applicable for object detection with variance of shape and surface texture, and existing local descriptors show limited ability to distinguish this kind of shape. A new object detection algorithm based on orientation descriptor is proposed. Initial descriptors are calculated based on silhouette of model or edge image of testing image, on this basis of which, orientation descriptor are calculated for each pixel in image. Orientation descriptor can describe edge orientation and tolerate small shape deformation. Multi-resolution method is utilized to speed up sliding-window algorithm. Descriptor matrixes of valid candidate region and model are matched to determine the existence of object at this position. The experimental results show that the proposed algorithm achieves fine detection rate relatively.