# Moving Object Detection for Event-based vision using Graph Spectral Clustering Source: [Moving Object Detection for Event-based vision using Graph Spectral Clustering]() Collection index: [llms.txt]() Data updated: 2025-12-24T16:42:59.443Z Authors: Anindya Mondal, Shashant R, Jhony H. Giraldo, Thierry Bouwmans, Ananda S. Chowdhury Published: 2021-09-30T10:19:22.000Z ## Abstract Moving object detection has been a central topic of discussion in computer vision for its wide range of applications like in self-driving cars, video surveillance, security, and enforcement. Neuromorphic Vision Sensors (NVS) are bio-inspired sensors that mimic the working of the human eye. Unlike conventional frame-based cameras, these sensors capture a stream of asynchronous 'events' that pose multiple advantages over the former, like high dynamic range, low latency, low power consumption, and reduced motion blur. However, these advantages come at a high cost, as the event camera data typically contains more noise and has low resolution. Moreover, as event-based cameras can only capture the relative changes in brightness of a scene, event data do not contain usual visual information (like texture and color) as available in video data from normal cameras. So, moving object detection in event-based cameras becomes an extremely challenging task. In this paper, we present an unsupervised Graph Spectral Clustering technique for Moving Object Detection in Event-based data (GSCEventMOD). We additionally show how the optimum number of moving objects can be automatically determined. Experimental comparisons on publicly available datasets show that the proposed GSCEventMOD algorithm outperforms a number of state-of-the-art techniques by a maximum margin of 30%. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [Moving Object Detection on Distsurf Hands (test)](): Moving Object Detection; Distsurf Hands (test); Recall: 90.68. - [Moving Object Detection on Distsurf Cars (test)](): Moving Object Detection; Distsurf Cars (test); Recall: 56.4. - [Moving Object Detection on Street](): Moving Object Detection; Street; Recall: 58.64. ## Original sources and implementation [Original paper]() [PDF]()