Cameras

1) Monochromatic Cameras (5 papers)

J. Silveira, C. Jung, S. Musse, “Background Subtraction and Shadow Detection in Grayscale Video Sequences”, XVIII Brazilian Symposium on Computer Graphics and Image Processing, SIBGRAPI 2005, pages 189-196, 2005.

J. Jacques, C. Jung, S. Musse, “A Background Subtraction Model Adapted to Illumination Changes”, International Conference on Image Processing, ICIP 2006, Atlanta, USA, October 2006.

C. Jung, “Efficient Background Subtraction and Shadow Removal for Monochromatic Video Sequences”, IEEE Transactions on Multimedia, pages 571-577, Volume 11, Issue 3, April 2009.

C. Blum, J. Jacques, G. Cavalheiro, H. Gerson Geraldo, C. Jung, S. Musse, “An Improved Background Subtraction Algorithm and Concurrent Implementations”, Parallel Processing Letters, Volume 20, No. 1, pages 71-89, 2010.

R. Sadykhov, S. Kuchuk, “Background subtraction in grayscale images algorithm”, International Conference on Intelligent Data Acquisition and Advanced Computing Systems, IDAACS 2013, pages 425-428, September 2013.

2) HD Cameras (7 papers)

M. Genovese, E. Napoli, “ASIC and FPGA Implementation of the Gaussian Mixture Model Algorithm for Real-Time Segmentation of High Definition Video”, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 2013.

M. Genovese, E. Napoli, “Processor core for real time background identification of HD video based on OpenCV Gaussian mixture model algorithm”, VLSI Circuits and Systems, May 2013.

M. Genovese, E. Napoli, D. De Caro, N. Petra, A. Strollo, “FPGA Implementation of Gaussian Mixture Model Algorithm for 47fps Segmentation of 1080p Video”, Journal of Electrical and Computer Engineering, Volume 2013, 2013.

Y. Zhao, D. Wu, J. Chen, J. Wang, “Background Modeling and Foreground Extraction Scheme for HD Traffic”, IEEE International Conference on Audio, Language and Image Processing, ICALIP 2014, Shangai, China, July 2014.

H. Tabkhi, M. Sabbagh, G. Schirner, “An Efficient Architecture Solution for Low-Power Real-Time Background Subtraction”, ASAP 2015, pages 218-225, 2015.

A. Beaugendre, S. Goto, “Block-propagative background subtraction system for UHDTV videos”, IPSJ Transactions on Computer Vision and Applications, 2015.

A. Beaugendre, S. Goto, “Adaptive Block-Propagative Background Subtraction Method for UHDTV Foreground Detection”, IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences Vol. E98-A, No.11, pages 2307-2314, November 2015.

A. Beaugendre, S. Goto, T. Yoshimura, “Real-Time UHD Background Modelling with Mixed Selection Block Updates”, IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol. E100.A, No. 2 pages 581-591, 2017.

3) Embbeded Cameras (3 papers)

Y. Shen, W. Hu, M. Yang, J. Liu, C. Chou, B. Wei, “Efficient Background Subtraction for Tracking in Embedded Camera Networks”, ACM/IEEE Conference on Information Processing in Sensor Networks, ISPN 2012, Beijing, China, April 2012.

Y. Shen, W. Hu, J. Liu, M. Yang, B. Wei, C. Chou, “Efficient Background Subtraction for Real-time Tracking in Embedded Camera Networks”, ACM Conference on Embedded Networked Sensor Systems, SenSys 2012, Toronto, Canada, November 2012.

R. Luo, Y. Wang, C. Chen, B. Yang, X. Guan, “Block compressed sensing based background subtraction for embedded smart camera”, Chinese Control Conference, CCC 2014, pages 4848-4853, July 2014.

4) IP Cameras (1 paper)

R. Zhang, X. Liao, J. Xu, “A Background Subtraction Algorithm Robust to Intensity Flicker Based on IP Camera”, Journal of Multimedia, Volume 9, No. 10, pages 1172-1179, October 2014.

5) Smart Cameras (1 paper)

M. Khan, A. Khan, C. Kyung, “EBSCam: Background Subtraction for Ubiquitous Computing”, IEEE Transactions on Very Large Scale Integration Systems ,VLSI 2016, pages 1-13, 2016.

6 - Cameras Trap (4 papers)

J. Giraldo-Zuluaga, A. Gomez, A. Salazar, A. Diaz-Pulido, “Camera-Trap Images Segmentation using Multi-Layer Robust Principal Component Analysis”, Preprint, January 2017.

M. Shakeri, H. Zhang, “Moving Object Detection in Time-Lapse or Motion Trigger Image Sequences using Low-rank and Invariant Sparse Decomposition”, IEEE International Conference on Computer Vision, ICCV 2017, October 2017.

H. Yousif, J. Yuan, R. Kays, Z. He, “Fast Human-Animal Detection from Highly Cluttered Camera-Trap Images using Joint Background Modeling and Deep Learning Classification”, IEEE International Symposium on Circuits and Systems, ISCAS 2017, pages 1-4, September 2017.

M. Janzen, K. Visser, D. Visscher, I. MacLeod, D. Vujnovic, K. Vujnovic “Semi-automated camera trap image processing for the detection of ungulate fence crossing events”, Environmental Monitoring and Assessment pages189-527, 2017.

7) Omnidirectional Cameras (2 papers)

T. Boult, R. Micheals, X. Gao, M. Eckmann, "Into the woods: visual surveillance of noncooperative and camouflaged targets in complex outdoor settings", Proceedings of the IEEE, Volume 89, No. 10, pages 1382-1402, October 2001.

K. Yamazawa, N. Yokoya, "Detecting moving objects from omnidirectional dynamic images based on adaptive background subtraction", IEEE International Conference on Image Processing, ICIP 2003, 2003.