ArticleFrontiers in neuroscience2020
Event-Based Gesture Recognition With Dynamic Background Suppression Using Smartphone Computational Capabilities.
Article in Frontiers in neuroscience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Comparison of Anomaly Detection Methods on Event-Based Vision Sensor Data in a High Noise Environment.Sensors (Basel, Switzerland) · 2026Article
- SpikingJelly: An open-source machine learning infrastructure platform for spike-based intelligence.Science advances · 2023Article
- Heterogeneous recurrent spiking neural network for spatio-temporal classification.Frontiers in neuroscience · 2023Article
- Precise Spiking Motifs in Neurobiological and Neuromorphic Data.Brain sciences · 2022Review
- μBrain: An Event-Driven and Fully Synthesizable Architecture for Spiking Neural Networks.Frontiers in neuroscience · 2021Article
- Is Neuromorphic MNIST Neuromorphic? Analyzing the Discriminative Power of Neuromorphic Datasets in the Time Domain.Frontiers in neuroscience · 2021Article
- Event-Based Gesture Recognition through a Hierarchy of Time-Surfaces for FPGA.Sensors (Basel, Switzerland) · 2020Article
- Event-Based Gesture Recognition With Dynamic Background Suppression Using Smartphone Computational Capabilities.Frontiers in neuroscience · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper, we introduce a framework for dynamic gesture recognition with background suppression operating on the output of a moving event-based camera. The system is developed to operate in real-time using only the computational capabilities of a mobile phone. It introduces a new development around the concept of time-surfaces. It also presents a novel event-based methodology to dynamically remove backgrounds that uses the high temporal resolution properties of event-based cameras. To our knowledge, this is the first Android event-based framework for vision-based recognition of
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Registered trials
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