Introduction to the Panoptic Studio Toolbox
The Panoptic Studio Toolbox is a robust collection of tools designed to work with data from the Panoptic Studio, a cutting-edge multiview system developed by the CMU-Perceptual-Computing-Lab. This toolbox facilitates downloading, processing, and visualizing the complex data associated with this advanced motion capture system. The Panoptic Studio Toolbox offers researchers and developers an efficient way to handle the immense datasets generated for analyzing human motion and interaction in 3D.
Key Features and Setup
Accessing the Toolbox
To begin using the Panoptic Studio Toolbox, users can clone the necessary code repository from GitHub. This requires basic git command-line operations to download and set up the toolbox framework:
git clone https://github.com/CMU-Perceptual-Computing-Lab/panoptic-toolbox
cd panoptic-toolbox
Data Downloading
One of the fundamental functionalities of the toolbox is data downloading. Users can fetch sample datasets or specific sequence data. A typical download example involves using a shell script to retrieve data by running:
./scripts/getData.sh 171204_pose1_sample
This command will create a directory for the dataset and populate it with various synchronized video files and calibration data essential for 3D keypoint analysis.
Dataset Options and Server Mirroring
A noteworthy convenience is the ability to switch data retrieval to the secondary SNU server if the primary CMU server is unavailable. This is done by adding an --snu-endpoint option to the download scripts. Users can tailor their downloads to include specific numbers of VGA and HD videos based on their research needs.
Extracting and Managing Data
Included scripts allow users to extract images and 3D keypoint data from downloaded datasets. The process utilizes ffmpeg for video processing, ensuring that both image files and skeletal data are easily accessible:
./scripts/extractAll.sh 171204_pose1_sample
These automated tasks are streamlined through commands that extract, organize, and prepare the dataset for immediate analysis and visualization.
Visualization and Data Analysis Tools
Python Visualization
For those utilizing Python in their studies, the toolbox includes Jupyter Notebook demos to visualize 3D keypoints related to body, face, and hand movements. This includes viewing positions in 3D space and reprojecting keypoints onto specific video views:
cd python
jupyter notebook demo_3Dkeypoints_3dview.ipynb
Extended Visualization Capabilities
The toolbox also supports OpenGL for more advanced visualization tasks through a separate Python script. Users must install pyopengl to leverage these features:
python glViewer.py
Matlab Support
Although the Matlab tools are referenced as outdated and do not support the latest 3D keypoint formats, they offer insights into foundational capabilities, serving as a legacy reference within the toolbox.
Data Structure and Output
The toolbox outputs are in JSON format providing highly detailed information about the skeletal structure, including unique identifiers for each subject and joint data in 3D space. The skeletal keys cover essential human motion points like neck, shoulders, hips, knees, and more, with confidence scores attached to each coordinate set.
Additional Resources and Updates
The Panoptic Studio Toolbox website offers a comprehensive suite of resources including example videos and interactive 3D viewers. Users also have access to extensive documentation, ensuring they can keep up with updates and new sequence releases.
Conclusion
The Panoptic Studio Toolbox is an essential resource for researchers involved in social motion capture, offering extensive functionality, customization, and support for large dataset handling. Its integration of both legacy systems and modern tools makes it a versatile platform for developing insights into human motion and interaction.