Changes between Version 16 and Version 17 of Hardware/Cameras


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Timestamp:
Apr 21, 2022, 9:15:03 PM (2 years ago)
Author:
zk2172
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  • Hardware/Cameras

    v16 v17  
    5151
    5252The YOLOv4 blurring model is trained in Darknet on the Mudd 1st floor video
    53 dataset annotated in Summer 2021. Deep learning models for detection and tracking have been converted from Darknet to PyTorch for
     53dataset annotated in Summer 2021. Deep learning models for detection and tracking have been converted from Darknet to Nvidia TensorRT for
    5454integration into the current implementation of the blurring pipeline.
    5555
    5656=== Reference Papers and DOI
    57 The following papers describe the project vision and key technologies as well as the development, deployment, and outreach efforts. We would appreciate it if you cite these papers when publishing results obtained using the COSMOS testbed.
     57The following papers describe the COSMOS project vision and key technologies relevant to the use of video cameras. We would appreciate it if you cite these papers when publishing results obtained using the COSMOS testbed.
    5858
    5959D. Raychaudhuri, I. Seskar, G. Zussman, T. Korakis, D. Kilper, T. Chen, J. Kolodziejski, M. Sherman, Z. Kostic, X. Gu, H. Krishnaswamy, S. Maheshwari, P. Skrimponis, and C. Gutterman, “Challenge: COSMOS: A city-scale programmable testbed for experimentation with advanced wireless,” in Proc. ACM MOBICOM’20, 2020." ​[https://wimnet.ee.columbia.edu/wp-content/uploads/2020/02/MobiCom2020_COSMOS.pdf (Download)] https://doi.org/10.1145/3372224.3380891
    6060
    61 P. Skrimponis, N. Makris, S. B. Rajguru, K. Cheng, J. Ostrometzky, E. Ford, Z. Kostic, G. Zussman, and T. Korakis, “Cosmos educational toolkit: Using experimental wireless networking to enhance middle/high school stem education,” SIGCOMM Comput. Commun. Rev., vol. 50, p. 58–65, oct 2020.
     61S. Yang, E. Bailey, Z. Yang, J. Ostrometzky, G. Zussman, I. Seskar, Z. Kostic, “COSMOS Smart Intersection: Edge Compute and Communications for Bird’s Eye Object Tracking,” IEEE Percom – Smart Edge 2020, 4th International Workshop on Smart Edge Computing and Networking, Mar. 2020. [https://wimnet.ee.columbia.edu/wp-content/uploads/2020/02/Smart_Intersection_COSMOS_SmartEdge2020.pdf (Download)] https://wimnet.ee.columbia.edu/wp-content/uploads/2020/02/Smart_Intersection_COSMOS_SmartEdge2020.pdf
    6262
    63 S. Yang, E. Bailey, Z. Yang, J. Ostrometzky, G. Zussman, I. Seskar, and Z. Kostic, “COSMOS smart intersection: Edge compute and communications for bird’s eye object tracking,” in Proc. SmartEdge, 2020.
    64 
    65 Z. Duan, Z. Yang, R. Samoilenko, D. S. Oza, A. Jagadeesan, M. Sun, H. Ye, Z. Xiong, G. Zussman, and Z. Kostic, “Smart city traffic intersection: Impact of video quality and scene complexity on precision and inference,” in Proc. IEEE Smart City’21, 2021.
    66 
    67 Z. Yang, M. Sun, H. Ye, Z. Xiong, G. Zussman, and Z. Kostic, “Birds eye view social distancing analysis system,” arXiv preprint:2112.07159, 2021.
    68 
    69 A. Angus et al., "Real-Time Video Anonymization in Smart City Intersections," in preparation.
    70 
    71 Z. Kostic, Alex Angus, Zhengye Yang, Zhuoxu Duan, Ivan Seskar, Gil Zussman, Dipankar Raychaudhuri, "Intelligence Nodes for Future Metropolises," in preparation.
     63Additional publications are listed at [https://drive.google.com/drive/u/0/folders/1SEsocAAIReepdjE4XyVyT4kiqrunv7BU].
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