The use of rendered images, whether from completely synthetic datasets or from 3D reconstructions, is increasingly prevalent in vision tasks. However, little attention has been given to how the selection of viewpoints affects the performance of rendered training sets. In this paper, we propose a data-driven approach to view set selection. Given a set of example images, we extract statistics des...

This paper focuses on pose estimation of 3D object from 2D images. The base system of Structure from Motion is applied. A 3D model with feature points and descriptors is prebuilt. 3D-2D matching is employed in recognition and pose estimation process. The method of pairwise correspondence is proposed. To reduce reprojection error of the model, a weighting step is added. Viewpoint change of camer...

Cryptography is an art and science of secure communication. Here the sender and receiver are guaranteed the security through encryption of their data, with the help of a common key. Both the parties should agree on this key prior to communication. The cryptographic systems which perform these tasks are designed to keep the key secret while assuming that the algorithm used for encryption and dec...

Abstract. In this paper we recall a non-standard construction of the Borel sigma-algebraB in [0, 1] and construct a family of measures (in particular, Lebesgue measure) in B by a completely non-topological method. This approach, that goes back to Steinhaus, in 1923, is now used to introduce natural generalizations of the concept of normal numbers and explore their intrinsic probabilistic proper...

In the case of ergodicity much of the structure of a one-dimensional time-discrete dynamical system is already determined by its ordinal structure. In order to explain this phenomenon more precisely, we show that ordinal patterns, which describe the up and down in the orbits of an ergodic Borel measurable map on a subset of the real numbers, are in a certain sense generating. On this base we gi...

Various kinds of software obfuscation methods have been proposed to protect security-sensitive information involved in software implementations. This paper proposes a cracker-centric approach to give a guideline for employing existing obfuscation methods to disrupt crackers’ actions.

Optimization has always played a central role in machine learning and advances in the field of optimization and mathematical programming have greatly influenced machine learning models. However the connection between optimization and learning is much deeper : one can phrase statistical and online learning problems directly as corresponding optimization problems. In this dissertation I take this...