Dataset: Occupancy Detection, Tracking, and Estimation Using a Vertically Mounted Depth Sensor
Creators
- 1. Carnegie Mellon University
- 2. Bosch Research & Technology Center
- 3. National University of Singapore
- 4. Lawrence Berkeley National Laboratory
Description
Occupancy detection, tracking, and estimation has a wide range of applications including improving building energy efficiency, safety, and security of the occupants. As depth sensors are getting cheaper, they offer a viable solution to estimate occupancy accurately in a non-privacy invasive manner. Even though there are publicly available depth datasets, they do not consider placing the sensor in the ceiling looking downwards to estimate occupancy. We deployed four Kinect for XBOX One in four CMU classrooms and conference rooms for a period of four weeks in 2017 and collected over 6 TB of depth data. We annotate this huge dataset by labelling bounding boxes around occupants and release the annotated dataset.
A sample of the dataset can be found here: https://doi.org/10.5281/zenodo.3457385
Notes
Files
Files
(13.8 GB)
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