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Fast Feature-Less Quaternion-based Particle Swarm Optimization for Object Pose Estimation From RGB-D Images

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Fast Feature-Less Quaternion-based Particle Swarm Optimization for Object Pose Estimation From RGB-D Images

The code in this repository is related to the original paper: http://www.bmva.org/bmvc/2016/papers/paper113/ and includes some improvements.

This is the GPU implementation, which includes object segmentation from https://arxiv.org/abs/1605.03746


Hardware:

Requires a CUDA enabled GPU (with support for CUDA 7.0 or greater)

Sofware:

  • OpenCV
  • gcc with support for c++11

Compile:

make

Run (estimate the pose of the first 15 detected object clusters):

for N in {0..15}; do; ./main object_model rgb_image depth_image $N; done

Where rgb_image and depth_image are 640x480 png images.

For tuning the object segmentation parameters for different datasets, it could be useful to use the code from https://github.com/morpheus1820/graph-canny-segm

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Fast Feature-Less Quaternion-based Particle Swarm Optimization for Object Pose Estimation From RGB-D Images

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