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Color Point Pair Feature Light

EasyChair Preprint no. 6833

13 pagesDate: October 10, 2021


Object recognition in the field of computer vision is a constant challenge to achieve better precision in less time. In this research, is proposed a new 3D descriptor, to work with depth cameras called CPPFL, based on the PPF descriptor from [1]. This proposed descriptor takes advantage of color information and groups it more effectively and lightly than the CPPF descriptor from [2], which uses the color information too. Also is proposed an alternative descriptor called CPPFL+, which differs in the construction taking advantage of the same concept of grouping colors, so it gains a “plus” in speed. This change makes the descriptor more efficient compared to PPF and CPPF descriptors. Optimizing the object recognition process [3], it can reach a rate of ten frames per second or more depending on the size of the object.

Keyphrases: 3D descriptor, object recognition, RGB-D cameras

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Luis Ronald Istaña Chipana and Manuel Eduardo Loaiza Fernández},
  title = {Color Point Pair Feature Light},
  howpublished = {EasyChair Preprint no. 6833},

  year = {EasyChair, 2021}}
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