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Online Object Detection and Localization on Stereo Visual SLAM System

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taihup/object-detection-sptam

 
 

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object-detection-sptam is a SLAM system for stereo cameras which builds a map of objects in a scene. The system is based on the SLAM method S-PTAM and an object detection module. The object detection module uses Deep Learning to perform online detection and provide the 3d pose estimations of objects present in an input image, while S-PTAM estimates the camera pose in real time.

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Related Publications:

[1] Taihú Pire, Javier Corti and Guillermo Grinblat. Online Object Detection and Localization on Stereo Visual SLAM System Journal of Intelligent & Robotic Systems, 2019.

Table of Contents

License

object-detection-sptam is released under GPLv3 license.

For a closed-source version of object-detection-sptam for commercial purposes, please contact the authors.

If you use object-detection-sptam in an academic work, please cite:

@article{pire2019object,
          title = {{Online Object Detection and Localization on Stereo Visual SLAM System}},
          author = {Pire, Taih{'u} and Corti, Javier and Grinblat, Guillermo},
          journal = {Journal of Intelligent {&} Robotic Systems},
          day = {27},
          month = {August},
          year = {2019},
          issn = {1573-0409},
          doi = {10.1007/s10846-019-01074-2}
}

Disclaimer

This site and the code provided here are under active development. Even though we try to only release working high quality code, this version might still contain some issues. Please use it with caution.

Dependencies

Move the content of ros directory (ros nodes and the network model that is used in rcnn_pose.py) to your ros workspace. Then compile the ros workspace.

py-faster-rcnn Dependencies

caffe-fast-rcnn

Tested on Ubuntu 16.01

sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libhdf5-serial-dev protobuf-compiler
sudo apt-get install --no-install-recommends libboost-all-dev
sudo apt-get install libgflags-dev libgoogle-glog-dev liblmdb-dev

Blas

sudo apt-get install libblas-dev liblapack-dev

ATLAS

sudo apt-get install libatlas-base-dev

Compile and Install Caffe

cp Makefile.config.example Makefile.config (revisar el Makefile.config y setear las variables necesarias) 
mkdir build
cd build
cmake ..
make -j4 && make pycaffe
make install

Compile py-faster-rcnn

cd ~/object-detection-sptam/py-faster-rcnn/lib
make

Install py-faster-rcnn

pip install --user easydict
pip install --user skimage
cd ~/.local/lib/python2.7/site-packages
ln -s ~/object-detection-sptam/py-faster-rcnn/caffe-fast-rcnn/build/install/python/caffe caffe
ln -s ~/object-detection-sptam/py-faster-rcnn/lib/fast_rcnn fast_rcnn
ln -s ~/object-detection-sptam/py-faster-rcnn/lib/utils utils
ln -s ~/object-detection-sptam/py-faster-rcnn/lib/nms nms
ln -s ~/object-detection-sptam/py-faster-rcnn/lib/rpn rpn
ln -s ~/object-detection-sptam/py-faster-rcnn/lib/datasets datasets
ln -s ~/object-detection-sptam/py-faster-rcnn/lib/roi_data_layer roi_data_layer
ln -s ~/object-detection-sptam/py-faster-rcnn/lib/pycocotools pycocotools
ln -s ~/object-detection-sptam/py-faster-rcnn/lib/transform transform

Modified S-PTAM Dependencies

SuiteSparse

sudo apt-get install libsuitesparse-dev

g2o

cd  ~/object-detection-sptam/dependencies/
source getG2o.sh
cd ~/object-detection-sptam/dependencies/g2o
mkdir build && cd build
cmake ..
make 
sudo make install

meta

sudo cp -Rf ~/object-detection-sptam/dependencies/meta/include/meta /usr/include/

pugixml

cd ~/object-detection-sptam/dependencies/pugixml
mkdir build
cd build
cmake ..
make
sudo make install/local

ApproxMVBB

cd ~/object-detection-sptam/dependencies/
source getApproxMVBB.sh 
cd  ~/object-detection-sptam/dependencies/ApproxMVBB
mkdir build
cd build 
cmake ..
make all
sudo make install

Compilation

catkin build sptam -DCMAKE_BUILD_TYPE=RelWithDebInfo -DSINGLE_THREAD=OFF -DSHOW_TRACKED_FRAMES=ON -DSHOW_PROFILING=ON -DPARALLELIZE=ON

Run

roslaunch sptam dl_zed.launch

On execution is going to ask:

~/.local/lib/python2.7/models/modelpose/VGG16/faster_rcnn_end2end/test.final.prototxt

that is in the models_tained directory:

models_tained/modelpose/VGG16/faster_rcnn_end2end/test.final.prototxt

copy or moved to python directory:

cp -Rf /data/object-detection-sptam/models_trained/* ~/.local/lib/python2.7/models/

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