Techniques for Still Image Scene Classification and Object Detection

  • Ville Viitaniemi
  • Jorma Laaksonen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4132)


In this paper we consider the interaction between different semantic levels in still image scene classification and object detection problems. We present a method where a neural method is used to produce a tentative higher-level semantic scene representation from low-level statistical visual features in a bottom-up fashion. This emergent representation is then used to refine the lower-level object detection results. We evaluate the proposed method with data from Pascal VOC Challenge 2006 image classification and object detection competition. The proposed techniques for exploiting global classification results are found to significantly improve the accuracy of local object detection.


Object Detection Object Class Image Scene Hierarchical Segmentation Visual Object Class 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ville Viitaniemi
    • 1
  • Jorma Laaksonen
    • 1
  1. 1.Laboratory of Computer and Information ScienceHelsinki University of TechnologyTKKFinland

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