Distributed image-based 3-D localization of camera sensor networks

Abstract—We consider the problem,of distributed estimation of the,poses,of N cameras,in a camera,sensor,network using,image,measurements,only. The relative rotation,and translation (up to a scale factor) between,pairs of neighboring cameras,can,be estimated,using,standard,computer,vision techniques. However, due to noise in the image measurements, these estimates,may,not,be globally consistent. We,address this problem,by,minimizing,a cost function,on SE(3), in a distributed,fashion,using a generalization,of the classical consensus,algorithm,for averaging,Euclidean data. We,also derive a condition for convergence, which relates the step-size of the consensus,algorithm,and,the degree,of the camera,network graph. While our methods,are designed,with the camera,sensor network application in mind, our results are applicable to other localization problems,in a more,general setting. We also provide synthetic simulations,to test the validity of our approach.