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Project Database
Project Reference: ITP/049/22LP
Project Title: Video Analytics Based Anomaly Detection for Prioritizing Severity of Defective Underground Stormwater Drains
Hosting Institution: LSCM R&D Centre (LSCM)
Abstract: This seed project aims to develop an automatic means based on unsupervised machine
learning, neural network computing, and computer vision techniques to analyze video
content filmed inside underground stormwater drains to help discover structural and
functional related anomalies. Such anomalies may jeopardize the integrity of the overall
protective infrastructure to maintain necessary slope safety from landslide, especially for
the densely populated hillside areas in Hong Kong. The R&D methodology involves the
use of deep learning methods to extract image features for vectorizing video imagery of
underground drains. Because of unavailability of concrete knowledge of how damages or
defects are presented inside different drains, unsupervised machine learning techniques
are used to cluster all vectorized images into various groups. The resulting image
clusters will then be visualized for identifying groups having damage-related issues and
subsequently computationally prioritize the severity of the defective drains to determine
the priority of remedial works. Hong Kong Housing Authority (HKHA) is one of the slope
management users to survey structural integrity of underground stormwater drains
beneath slopes surrounding around 130 hillside public housing estates. The project is
planned to use HKHA’s drain videos as the basis for developing a prototype tool to help
detect damages or anomalies. The resulting anomaly detection capability may help crossvalidate
the consistency of manual survey results and the viewability of manually
captured drain videos. The R&D work may lead to more opportunities to apply such
anomaly detection video analytics to help strengthen quality-related issues from
surveying video data of underlying facilities for preservation and safety purposes.
Project Coordinator: Dr Dorbin Ng
Approved Funding Amount: HK$ 2.76 M
Project Period: 1 Feb 2023 - 30 April 2024
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