Object pose estimation in underwater acoustic images
We address the problem of the recognition of man-made objects and the estimation of the related orientation in 2D acoustic images acquired with a forward looking sonar or an acoustic camera. A voting-based approach is described that is able to recognize objects and to estimate their two-dimensional pose by using information coming from boundary segments and their angular relations. The method is directly applied to the edge discontinuities of underwater acoustic images, whose quality is usually affected by some undesired effects such as object blurring, speckle noise, and geometrical distortions degrading the edge detection. The voting approach is robust with respect to these effects, so that good results are obtained even with images of poor quality. The sequences of simulated and real acoustic images are presented in order to test the validity of the proposed method in terms of the average estimation error and computational load.