Fast Detection of Multiple Textureless 3-D Objects

  • Hongping Cai
  • Tomáš Werner
  • Jiří Matas
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7963)

Abstract

We propose a fast edge-based approach for detection and approximate pose estimation of multiple textureless objects in a single image. The objects are trained from a set of edge maps, each showing one object in one pose. To each scanning window in the input image, the nearest neighbor is found among these training templates by a two-level cascade. The first cascade level, based on a novel edge-based sparse image descriptor and fast search by index table, prunes the majority of background windows. The second level verifies the surviving detection hypotheses by oriented chamfer matching, improved by selecting discriminative edges and by compensating a bias towards simple objects. The method outperforms the state-of-the-art approach by Damen et al. (2012). The processing is near real-time, ranging from 2 to 4 frames per second for the training set size ~104.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Hongping Cai
    • 1
  • Tomáš Werner
    • 1
  • Jiří Matas
    • 1
  1. 1.Center for Machine PerceptionCzech Technical UniversityPragueCzech Republic

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