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A Review of methods for Textureless Object Recognition
Textureless object recognition has become a significant task in Computer
Vision with the advent of Robotics and its applications in manufacturing
sector. It has been very challenging to get good performance because of its
lack of discriminative features and reflectance properties. Hence, the
approaches used for textured objects cannot be applied for textureless objects.
A lot of work has been done in the last 20 years, especially in the recent 5
years after the TLess and other textureless dataset were introduced. In our
research, we plan to combine image processing techniques (for feature
enhancement) along with deep learning techniques (for object recognition). Here
we present an overview of the various existing work in the field of textureless
object recognition, which can be broadly classified into View-based,
Feature-based and Shape-based. We have also added a review of few of the
research papers submitted at the International Conference on Smart Multimedia,
2018. Index terms: Computer Vision, Textureless object detection, Textureless
object recognition, Feature-based, Edge detection, Deep LearningComment: 25 page