MSR Vision Faculty Summit – Machine Learning for Visual Recognition: Randomised Decision Forests and Its Novel Applications

This talk begins with a quick overview of machine learning techniques we study for visual recognition. Challenges occur due to high-dimensional space and significant intraclass data variations, which demand good generalisation to unseen data. Among state-of-the-art techniques, we emphasise Randomised Decision Forests and tree-structured methods. Following concepts and principles, their applications are demonstrated for challenging novel problems: real-time action recognition, object phenotype recognition using 3D shape priors, and video-based object recognition, that we recently tackled at Imperial College jointly with Univ. of Cambridge.

Date:
Speakers:
Tae-Kyun Kim
Affiliation:
Imperial College
    • Portrait of Jeff Running

      Jeff Running