Latent Layout Analysis (LLA) is a novel unsupervised learning technique to discover objects in unseen images using a set of un-annotated training images. LLA defines a generative ...
Recognizing a person’s motion is intuitive for humans but represents a challenging problem in machine vision. In this paper, we present a multi-disciplinary framework for recogn...
This paper introduces an affine invariant shape descriptor for maximally stable extremal regions (MSER). Affine invariant feature descriptors are normally computed by sampling the...
Use of IR images is advantageous for many surveillance applications where the systems must operate around the clock and external illumination is not always available. We investiga...
We propose a method for the analysis of Magnetic Resonance (MR) cardiac images with the goal of reconstructing the motion of the ventricular walls. The main feature of our method i...