Human body registration is an important and complex problem that can be found in a variety of real world applications. Registration maps images of a person obtained from different camera views into a common reference system of a scene that contains a human figure. The complexity of the problem stems from the fact that human body can arbitrarily move in the 3-D space while changing its own shape. The registration task is stated as a nonlinear global multimodal optimization problem, i.e., as a search for a proper transformation that provides the best match between the images of the body and the scene. The paper describes an approach to human body registration that utilizes a hybrid evolutionary algorithm and image response analysis. Hybrid evolutionary algorithm provides an efficient procedure of global search in extremely large parameter space. Image response analysis allows to reduce the total amount of information that has to be processed during evaluation of potential solutions. In the process of the evolutionary search, response matrix of each template image is compared against response matrix of the reference image of the scene, in order to find the correct mapping between the images. The efficiency of the proposed approach is demonstrated on a test set of 2-D grayscale images.