2024/09/22 by Maria Zafeiri, Georgios Evangelidis, Zafeiri, Maria +3
Computer Science · Engineering · #68T45 #68U10 #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #I.4.8 #I.4.9 #I.5.4 #Low-power high-performance VLSI design #Parallel Computing and Optimization Techniques #Radiation Effects in Electronics
paper · pdf · doi:10.48550/arxiv.2409.14564
openalex publication_date 2024/09/22 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper, an event-based tracker is presented. Inspired by recent advances in asynchronous processing of individual events, we develop a direct matching scheme that aligns spatial distributions of events at different times. More specifically, we adopt the Enhanced Correlation Coefficient (ECC) criterion and propose a tracking algorithm that computes a 2D motion warp per single event, called event-ECC (eECC). The complete tracking of a feature along time is cast as a single iterative continuous optimization problem, whereby every single iteration is executed per event. The computational burden of event-wise processing is alleviated through a lightweight version that benefits from incremental processing and updating scheme. We test the proposed algorithm on publicly available datasets and we report improvements in tracking accuracy and feature age over state-of-the-art event-based asynchronous trackers.