Urban object recognition from informative local features

Gerald Fritz, Christin Seifert, Lucas Paletta

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

22 Citations (Scopus)


Autonomous mobile agents require object recognition for high level interpretation and localization in complex scenes. In urban environments, recognition of buildings might play a dominant role in robotic systems that need object based navigation, that take advantage of visual feedback and multimodal information for self-localization, or that enable association to related information from the identified semantics. We present a new method – the informative local features approach – based on an information theoretic saliency measure that is rapidly derived from a local Parzen window density estimation in feature subspace. From the learning of a decision tree based mapping to informative features, it enables attentive access to discriminative information and thereby significantly speeds up the recognition process. This approach is highly robust with respect to severe degrees of partial occlusion, noise, and tolerant to some changes in scale and illumination. We present performance evaluation on our publicly available reference object database (TSG-20) that demonstrates the efficiency of this approach, case wise even outperforming the SIFT feature approach [1]. Building recognition will be advantageous in various application domains, such as, mobile mapping, unmanned vehicle navigation, and systems for car driver assistance.
Original languageEnglish
Title of host publicationProceedings of the 2005 IEEE International Conference on Robotics and Automation
Subtitle of host publication18-22 April 2005, Barcelona, Spain
Number of pages7
ISBN (Print)0-7803-8914-X
Publication statusPublished - 2005
Externally publishedYes
Event2005 IEEE International Conference on Robotics and Automation, ICRA 2005 - Barcelona, Spain
Duration: 18 Apr 200522 Apr 2005

Publication series

NameProceedings IEEE International Conference on Robotics and Automation (ICRA)
ISSN (Print)1050-4729


Conference2005 IEEE International Conference on Robotics and Automation, ICRA 2005
Abbreviated titleICRA


  • Object recognition
  • Outdoor computer vision
  • Urban environments
  • Visual attention


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