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Cameras
Installed Cameras Information
Hikvision DS-2CD5585G0-IZHS
Mudd floor 1, towards 120th street Mudd first floor Mech E lab https://www.hikvision.com/uploadfile/image/11769_DatasheetofDS2CD5585G0IZ(H)S.pdf
Hikvision DS-2CD5585G0-IZHS
Mudd 2nd floor, towards Amsterdam balcony camera
Hikvision DS-2CD4AC5F-IZH
12MP Outdoor Network Bullet Camera with Night Vision, 2.8-12mm Lens & Built-In Heater S/N: 212528616: 20191015: installation in Botwinick lab mudd1224, towards 120th street
Hikvision DS-2CD5585G0-IZHS
2.8mm-12mm (8MP) Mudd 12thFloor Balcony towards Amsterdam Avenue
COSMOS Cameras Data-set
1st-floor videos (anonymized*): https://drive.google.com/drive/u/0/folders/1QXrfsLXEKfRfQyc6qzvtg37A0Z1i0io5
2nd-floor videos (anonymized*): https://drive.google.com/drive/u/0/folders/1LR7H4theRazz2_uYHvCFGVVewQmKbWSF
12th-floor videos (120th street): https://drive.google.com/drive/u/0/folders/1SEsocAAIReepdjE4XyVyT4kiqrunv7BU
12th-floor videos (Amsterdam Avenue): https://drive.google.com/drive/u/0/folders/1qC-62s8ohTGg-odyzo7BNw2GDv1OIeoK
Videos in this directory are outputs of the COSMOS YOLOv4 blurring pipeline.
Faces and license plates are anonymized with Gaussian blurred areas defined by bounding box detection coordinates. A high-level overview of the blurring.
*Anonymization workflow:
- Frames are read individually from a video file.
- Each frame is then:
2.1 Resized to the input size of the specific YOLOv4 model (960x960 or 1440x1440)
2.2 Passed through the YOLOv4 model which outputs bounding box predictions
2.3 Blurred corresponding to the bounding box predictions
- Blurred frames are written to the output video file.
The YOLOv4 blurring model is trained in Darknet on the Mudd 1st floor video dataset annotated in Summer 2021. Models are converted from Darknet to Py Torch for integration into the current implementation of the blurring pipeline.
