Object Detection and Classification for Street Cleanliness
Description
In collaboration with the Sanitation Department of LA, IMSC has been developing a framework to automatically detect the cleanliness of streets as well as any special objects in need of removal. The framework makes use of machine learning technology trained on images/videos collected by the city and/or taken by citizens. The images taken by mobile cameras (e.g., LA City’s garbage collection trucks and/or citizens’ smartphones using our own MediaQ App) are transferred to the MediaQ server, then these images can be automatically classified based on predefined cleanliness indexes and object types (such as bulky item, illegal dumping). In this project, we will focus on the detection and classification of homeless encampments in LA streets. Recorded images/videos with GPS location data will be processed and the classification results will be displayed on a map to understand the distribution of homeless people in LA, which is essential data to study the homeless issue.
Students
Advisors
Skills Required by the team
- Python
- Machine Learning
- Data Visualization
- Computer Vision