Apart from a tool or development environment for heterogeneous CPU/GPU programming, Quasar is also an extensive research project. We are working intensively to apply Quasar to various application domains and to make Quasar even better!
Below is an overview of scientific publications related to Quasar and/or applications realized using Quasar.
- M. Nourazar and B. Goossens, “Accelerating Iterative CT Reconstruction Algorithms using Tensor Cores, ” Journal of Real-Time Image Processing, 2021, p.1-13.
- J. Roels, F. Vernaillen, A. Kremer, A. Gonçalves, J. Aelterman, H. Q. Luong, B. Goossens, W. Philips, S. Lippens and Y. Saeys, “DenoisEM: An Interactive ImageJ Plugin for Semi-automated Image Denoising in Electron Microscopy,” Nature Communications, 11, nr 771, Feb 2020.
- B. Goossens, D. Labate and B. Bodmann, “Robust and Stable Region-Of-Interest CT Reconstruction by Sparsity Inducing Convex Optimization,” Inverse Problems and Imaging, 14 (2), p. 291-316, April 2020. Preprint
- V. Avramelos, R. Verhack, I. Saenen, G. Van Wallendael, B. Goossens and P. Lambert, “Highly Parallel Steered Mixture-of-Experts Rendering at Pixel-Level for Image and Light Field Data,” Journal of Real-Time Image Processing (2018)
Dimitrievski, Martin, Peter Veelaert, and Wilfried Philips. “Behavioral Pedestrian Tracking Using a Camera and LiDAR Sensors on a Moving Vehicle.” Sensors 19.2 (2019): 391.
- B. Goossens, “Dataflow Management, Dynamic Load Balancing and Concurrent Processing for Real-time Embedded Vision Applications using Quasar,” International Journal of Circuit Theory and Applications, Special Issue of Computational Image Sensors and Smart Camera Hardware, Aug. 2018 p1-23.
- B. Goossens, H. Luong, J. Aelterman and W. Philips, “Quasar, a High-level Programming Language and Development Environment for Designing Smart Vision Systems on Embedded Platforms”, Designing Autonomous Systems Day at DATE 2018, Special session on “Smart Vision systems”, March 19-23, 2018, Dresden, Germany, p.1316-1321. Slides
- Dimitrievski, Martin, Peter Veelaert, and Wilfried Philips. “Semantically aware multilateral filter for depth upsampling in automotive LiDAR point clouds.” Intelligent Vehicles Symposium (IV), 2017 IEEE. IEEE, 2017.
- B. Goossens, H. Luong and W. Philips, “GASPACHO: a Generic Automatic Solver using Proximal Algorithms for Convex Huge Optimization problems,” Wavelets and Sparsity XVII, SPIE Optics & Photonics 2017, Aug. 6-10, 2017, San Diego, CA, USA.
- M. Dimitrievski, B. Goossens, P. Veelaert and W. Philips, “High resolution depth reconstruction from monocular images and sparse point clouds using deep convolutional network,” Applications of Digital Image Processing XL, SPIE Optics & Photonics 2017, Aug. 7-10, 2017, San Diego, CA, USA.
- S. Donné, H. Luong, B. Goossens and W. Philips, “Robust plane-based calibration for linear cameras,” Proc. IEEE Int. Conf Image Processing 2017 (ICIP2017), Sept. 17-20, Beijing, China (accepted).
- Donné, S., De Vylder, J., Goossens, B., & Philips, W. (2016). MATE: Machine Learning for Adaptive Calibration Template Detection. Sensors, 16(11), 1858.
- Roels, J., Aelterman, J., De Vylder, J., Lippens, S., Luong, H. Q., Guérin, C. J., & Philips, W. (2016). Image Degradation in Microscopic Images: Avoidance, Artifacts, and Solutions. In Focus on Bio-Image Informatics (pp. 41-67). Springer International Publishing.
- M. Dimitrievski, D. Van Hamme, P. Veelaert, W. Philips (2016), “Robust Matching of Occupancy Maps for Odometry in Autonomous Vehicles”, in Proceedings of the 11th Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP), pp. 626-633.
- J. De Vylder, D. Van Haerenborgh, J. Roels and B. Goossens, “Quasar tutorial: High-level programming of Heterogeneous Hardware,” HiPEAC 2016, Jan. 18-20, 2016, Prague.
- J. De Vylder, S. Donné, D. Van Haerenborgh and B. Goossens, “Real-time Machine Vision with GPU-acceleration using Quasar,” IS&T Electronic Imaging, Feb. 14-18, 2016, San Francisco, CA, USA.
- B. Goossens, S. Donné, J. Aelterman, J. De Vylder, D. Van Haerenborgh and W. Philips, “Real-time depth estimation and view interpolation using Quasar,” IS&T Electronic Imaging, Feb. 14-18, 2016, San Francisco, CA, USA.
- D. Van Haerenborgh, J. De Vylder and B. Goossens, “Quasar : rapid prototyping for image/video processing on heterogeneous hardware,” Int. Conf. Acoust. Speech and Signal Proc. (ICASSP), Mar. 20-25, 2016, Shanghai, China.
- M. Vlaminck, H. Luong, H. Vu, P. Veelaert and W. Philips. “Indoor assistance for visually impaired people using a RGB-D camera.” 2016 IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI). IEEE, 2016.
- Luong, H. Q., Vlaminck, M., Goeman, W., & Philips, W. (2016, July). Consistent ICP for the registration of sparse and inhomogeneous point clouds. In Communications and Electronics (ICCE), 2016 IEEE Sixth International Conference on (pp. 262-267). IEEE.
- Donné, S., Aelterman, J., Goossens, B., & Philips, W. (2015, October). Fast and Robust Variational Optical Flow for High-Resolution Images Using SLIC Superpixels. In International Conference on Advanced Concepts for Intelligent Vision Systems (pp. 205-216). Springer International Publishing.
- Roels, J., De Vylder, J., Saeys, Y., Goossens, B., & Philips, W. (2016, October). Decreasing Time Consumption of Microscopy Image Segmentation Through Parallel Processing on the GPU. In International Conference on Advanced Concepts for Intelligent Vision Systems (pp. 147-159). Springer International Publishing.
- B. Goossens, J. De Vylder, S. Donné and W. Philips, “Demo: Quasar – a New Programming Framework for Real-Time Image/Video Processing on GPU and CPU,” in Ninth International Conference on Distributed Smart Cameras (ICDSC 2015), Seville, Spain, Sept. 8-11, 2015, p. 205-206.
- B. Goossens, J. De Vylder and W. Philips, “Quasar – a New Heterogeneous Programming Framework for Image and Video Processing Algorithms on CPU and GPU, ” IEEE Int. Conf. on Image Processing (ICIP2014), Oct. 27-30, 2014, Paris, France, p. 2183-2185.