@inproceedings{AlhwarinFerreinGebhardtetal.2015,
  author    = {Alhwarin, Faraj and Ferrein, Alexander and Gebhardt, Andreas and Kallweit, Stephan and Scholl, Ingrid and Tedjasukmana, Osmond Sanjaya},
  title     = {Improving additive manufacturing by image processing and robotic milling},
  series = {2015 IEEE International Conference on Automation Science and Engineering (CASE), Aug 24-28, 2015 Gothenburg, Sweden},
  booktitle = {2015 IEEE International Conference on Automation Science and Engineering (CASE), Aug 24-28, 2015 Gothenburg, Sweden},
  doi       = {10.1109/CoASE.2015.7294217},
  pages     = {924 -- 929},
  year      = {2015},
  language  = {en}
}
@article{AlhwarinFerreinScholl2014,
  author    = {Alhwarin, Faraj and Ferrein, Alexander and Scholl, Ingrid},
  title     = {IR stereo kinect: improving depth images by combining structured light with IR stereo},
  pages     = {1 -- 9},
  year      = {2014},
  language  = {en}
}
@incollection{AlhwarinFerreinScholl2014,
  author    = {Alhwarin, Faraj and Ferrein, Alexander and Scholl, Ingrid},
  title     = {IR stereo kinect: improving depth images by combining structured light with IR stereo},
  series = {PRICAI 2014: Trends in artificial intelligence : 13th Pacific Rim International Conference on Artificial Intelligence : Gold Coast, QLD, Australia, December 1-5, 2014 : proceedings. (Lecture notes in computer science ; vol. 8862)},
  booktitle = {PRICAI 2014: Trends in artificial intelligence : 13th Pacific Rim International Conference on Artificial Intelligence : Gold Coast, QLD, Australia, December 1-5, 2014 : proceedings. (Lecture notes in computer science ; vol. 8862)},
  publisher = {Springer},
  address   = {M{\"u}nchen},
  isbn      = {978-3-319-13559-5 (Print) ; 978-3-319-13560-1 (E-Book)},
  doi       = {10.1007/978-3-319-13560-1_33},
  pages     = {409 -- 421},
  year      = {2014},
  abstract  = {RGB-D sensors such as the Microsoft Kinect or the Asus Xtion are inexpensive 3D sensors. A depth image is computed by calculating the distortion of a known infrared light (IR) pattern which is projected into the scene. While these sensors are great devices they have some limitations. The distance they can measure is limited and they suffer from reflection problems on transparent, shiny, or very matte and absorbing objects. If more than one RGB-D camera is used the IR patterns interfere with each other. This results in a massive loss of depth information. In this paper, we present a simple and powerful method to overcome these problems. We propose a stereo RGB-D camera system which uses the pros of RGB-D cameras and combine them with the pros of stereo camera systems. The idea is to utilize the IR images of each two sensors as a stereo pair to generate a depth map. The IR patterns emitted by IR projectors are exploited here to enhance the dense stereo matching even if the observed objects or surfaces are texture-less or transparent. The resulting disparity map is then fused with the depth map offered by the RGB-D sensor to fill the regions and the holes that appear because of interference, or due to transparent or reflective objects. Our results show that the density of depth information is increased especially for transparent, shiny or matte objects.},
  language  = {en}
}
@inproceedings{AlhwarinFerreinScholl2018,
  author    = {Alhwarin, Faraj and Ferrein, Alexander and Scholl, Ingrid},
  title     = {CRVM: Circular Random Variable-based Matcher - A Novel Hashing Method for Fast NN Search in High-dimensional Spaces},
  series = {Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2018},
  booktitle = {Proceedings of the 7th International Conference on Pattern Recognition Applications and Methods, ICPRAM 2018},
  isbn      = {978-989-758-276-9},
  doi       = {10.5220/0006692802140221},
  pages     = {214 -- 221},
  year      = {2018},
  language  = {en}
}
@inproceedings{AlhwarinFerreinScholl2019,
  author    = {Alhwarin, Faraj and Ferrein, Alexander and Scholl, Ingrid},
  title     = {An Efficient Hashing Algorithm for NN Problem in HD Spaces},
  series = {Lecture Notes in Computer Science},
  booktitle = {Lecture Notes in Computer Science},
  isbn      = {978-303005498-4},
  doi       = {10.1007/978-3-030-05499-1_6},
  pages     = {101 -- 115},
  year      = {2019},
  language  = {en}
}
@inproceedings{AlhwarinSchifferFerreinetal.2018,
  author    = {Alhwarin, Faraj and Schiffer, Stefan and Ferrein, Alexander and Scholl, Ingrid},
  title     = {Optimized KinectFusion Algorithm for 3D Scanning Applications},
  series = {Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: BIOIMAGING},
  booktitle = {Proceedings of the 11th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: BIOIMAGING},
  isbn      = {978-989-758-278-3},
  doi       = {10.5220/0006594700500057},
  pages     = {50 -- 57},
  year      = {2018},
  language  = {en}
}
@inproceedings{AlhwarinSchifferFerreinetal.2019,
  author    = {Alhwarin, Faraj and Schiffer, Stefan and Ferrein, Alexander and Scholl, Ingrid},
  title     = {An Optimized Method for 3D Body Scanning Applications Based on KinectFusion},
  series = {Communications in Computer and Information Science},
  volume    = {1024},
  booktitle = {Communications in Computer and Information Science},
  publisher = {Springer},
  issn      = {1865-0929},
  doi       = {10.1007/978-3-030-29196-9_6},
  pages     = {100 -- 113},
  year      = {2019},
  language  = {en}
}