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# Perceiving Humans: from Monocular 3D Localization to Social Distancing # Perceiving Humans: from Monocular 3D Localization to Social Distancing
![social distancing](docs/social_distancing.jpg)
> Perceiving humans in the context of Intelligent Transportation Systems (ITS) > Perceiving humans in the context of Intelligent Transportation Systems (ITS)
often relies on multiple cameras or expensive LiDAR sensors. often relies on multiple cameras or expensive LiDAR sensors.
In this work, we present a new cost- effective vision-based method that perceives humans’ locations in 3D In this work, we present a new cost- effective vision-based method that perceives humans’ locations in 3D
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Indeed, we show that we can rethink the concept of “social distancing” as a form of social interaction Indeed, we show that we can rethink the concept of “social distancing” as a form of social interaction
in contrast to a simple location-based rule. We publicly share the source code towards an open science mission. in contrast to a simple location-based rule. We publicly share the source code towards an open science mission.
This readme is in Beta version and refers to the `update` branch. It is currently under development.
## Predictions ## Predictions
For a quick setup download a pifpaf and a MonoLoco++ models from TODO and save them into `data/models`. For a quick setup download a pifpaf and a MonoLoco++ models from TODO and save them into `data/models`.
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An example from the Collective Activity Dataset is provided below. An example from the Collective Activity Dataset is provided below.
<img src="frame0038.jpg" width="600"/> <img src="frame0038.jpg" width="500"/>
To visualize social distancing run the below, command: To visualize social distancing run the below, command:
``` ```
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--output_types front bird --show_all \ --output_types front bird --show_all \
--model data/models/monoloco_pp-201203-1424.pkl -o <output directory> --model data/models/monoloco_pp-201203-1424.pkl -o <output directory>
``` ```
<img src="out_frame0038.jpg.front.png" width="500"/> <img src="out_frame0038.jpg.front.png" width="400"/>
<img src="out_frame0038.jpg.bird.png" width="500"/> <img src="out_frame0038.jpg.bird.png" width="400"/>
Threshold distance and radii (for F-formations) can be set using `--threshold-dist` and `--radii`, respectively.
For more info, run:
`python -m monstereo.run predict --help`
### Orientation and Bounding Box dimensions ### Orientation and Bounding Box dimensions
MonoLoco++ estimates orientation and box dimensions as well. Results are saved in a json file when using the command MonoLoco++ estimates orientation and box dimensions as well. Results are saved in a json file when using the command