ArticleFrontiers in neuroscience2016
Evaluation of Event-Based Algorithms for Optical Flow with Ground-Truth from Inertial Measurement Sensor.
Article in Frontiers in neuroscience, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- Event-Based Vision Application on Autonomous Unmanned Aerial Vehicle: A Systematic Review of Prospects and Challenges.Sensors (Basel, Switzerland) · 2025Review
- Hardware, Algorithms, and Applications of the Neuromorphic Vision Sensor: A Review.Sensors (Basel, Switzerland) · 2025Review
- Recurrent models of orientation selectivity enable robust early-vision processing in mixed-signal neuromorphic hardware.Nature communications · 2025Article
- TDE-3: an improved prior for optical flow computation in spiking neural networks.Frontiers in neuroscience · 2025Article
- Finding the gap: neuromorphic motion-vision in dense environments.Nature communications · 2024Article
- Accuracy and Speed Improvement of Event Camera Motion Estimation Using a Bird's-Eye View Transformation.Sensors (Basel, Switzerland) · 2022Article
- Neuromorphic Engineering Needs Closed-Loop Benchmarks.Frontiers in neuroscience · 2022Review
- Optical Flow Estimation by Matching Time Surface with Event-Based Cameras.Sensors (Basel, Switzerland) · 2021Article
- Probabilistic Spike Propagation for Efficient Hardware Implementation of Spiking Neural Networks.Frontiers in neuroscience · 2021Article
- A Benchmark Environment for Neuromorphic Stereo Vision.Frontiers in robotics and AI · 2021Article
- Event-Based Sensing and Signal Processing in the Visual, Auditory, and Olfactory Domain: A Review.Frontiers in neural circuits · 2021Review
- Event-Based Feature Extraction Using Adaptive Selection Thresholds.Sensors (Basel, Switzerland) · 2020Article
- Time-of-Travel Methods for Measuring Optical Flow on Board a Micro Flying Robot.Sensors (Basel, Switzerland) · 2017Article
- Conversion of Continuous-Valued Deep Networks to Efficient Event-Driven Networks for Image Classification.Frontiers in neuroscience · 2017Article
- Rendering visual events as sounds: Spatial attention capture by auditory augmented reality.PloS one · 2017Article
- DVS Benchmark Datasets for Object Tracking, Action Recognition, and Object Recognition.Frontiers in neuroscience · 2016Article
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2 authors.
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Abstract
In this study we compare nine optical flow algorithms that locally measure the flow normal to edges according to accuracy and computation cost. In contrast to conventional, frame-based motion flow algorithms, our open-source implementations compute optical flow based on address-events from a neuromorphic Dynamic Vision Sensor (DVS). For this benchmarking we created a dataset of two synthesized and three real samples recorded from a 240 × 180 pixel Dynamic and Active-pixel Vision Sensor (DAVIS). This dataset contains events from the DVS as well as conventional frames to support testing state-of-the-art frame-based methods. We introduce a new source for the ground truth: In the special case that the perceived motion stems solely from a rotation of the vision sensor around its three camera axes, the true optical flow can be estimated using gyro data from the inertial measurement unit integrated with the DAVIS camera. This provides a ground-truth to which we can compare algorithms that measure optical flow by means of motion cues. An analysis of error sources led to the use of a refractory period, more accurate numerical derivatives and a Savitzky-Golay filter to achieve significant improvements in accuracy. Our pure Java implementations of two recently published algorithms reduce computational cost by up to 29% compared to the original implementations. Two of the algorithms introduced in this paper further speed up processing by a factor of 10 compared with the original implementations, at equal or better accuracy. On a desktop PC, they run in real-time on dense natural input recorded by a DAVIS camera.
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