- author = "Juergen Leitner and Simon Harding and Pramod Chandrashekhariah and Mikhail Frank and Alexander Foerster and Jochen Triesch and Juergen Schmidhuber",
- title = "Learning visual object detection and localisation using icVision",
- journal = "Biologically Inspired Cognitive Architectures",
- year = "2013",
- volume = "5",
- pages = "29--41",
- month = jul,
- note = "Extended versions of selected papers from the Third Annual Meeting of the BICA Society (BICA 2012)",
- keywords = "genetic algorithms, genetic programming, Cartesian Genetic Programming, Humanoid robots, iCub, cartesianController, Computer vision, Perception, Cognition, Learning, Object detection",
- ISSN = "2212-683X",
-
URL = "
http://www.sciencedirect.com/science/article/pii/S2212683X13000443",
-
DOI = "
doi:10.1016/j.bica.2013.05.009",
- size = "13 pages",
- abstract = "Building artificial agents and robots that can act in an intelligent way is one of the main research goals in artificial intelligence and robotics. Yet it is still hard to integrate functional cognitive processes into these systems. 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 cognitive robotics research. It aims to mimic processes in the human brain performing visual cognition tasks. 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 fully autonomous learning of visual object representations. Furthermore localising the detected objects in 3D space is presented, which in turn can be used to create a model of the environment.",
-
notes = "a Dalle Molle Institute for Artificial Intelligence
(IDSIA)/SUPSI/USI, Manno-Lugano, Switzerland b Machine
Intelligence Ltd., South Zeal, United Kingdom c
Frankfurt Institute of Advanced Studies (FIAS),
Frankfurt am Main, Germany
Also known as \cite{Leitner201329}",
