Learning visual object detection and localisation using icVision

Jürgen Leitner, Simon Harding, Pramod Chandrashekhariah, Mikhail Frank, Alexander Förster, Jochen Triesch, Jürgen Schmidhuber
2013 Biologically Inspired Cognitive Architectures  
We present a framework combining computer vision and machine learning for the learning of object recognition in humanoid robots. A biologically inspired, bottom-up architecture is introduced to facilitate visual perception and cognitve robotics research. A number of experiments with this icVision framework are described. We showcase both detection and identification in the image plane (2D), using machine learning. In addition we show how a biologically inspired attention mechanism allows for
more » ... ly autonomous learning. Furthermore localising those objects in 3D space is shown, which in turn can be used to create a model of the environment.
doi:10.1016/j.bica.2013.05.009 fatcat:tfyx6y6azzfylfvu7tabbdponu