1 research outputs found
Feature Fusion using Extended Jaccard Graph and Stochastic Gradient Descent for Robot
Robot vision is a fundamental device for human-robot interaction and robot
complex tasks. In this paper, we use Kinect and propose a feature graph fusion
(FGF) for robot recognition. Our feature fusion utilizes RGB and depth
information to construct fused feature from Kinect. FGF involves multi-Jaccard
similarity to compute a robust graph and utilize word embedding method to
enhance the recognition results. We also collect DUT RGB-D face dataset and a
benchmark datset to evaluate the effectiveness and efficiency of our method.
The experimental results illustrate FGF is robust and effective to face and
object datasets in robot applications.Comment: Assembly Automatio