298 citations · 853 across the 29 of their papers we have counts for
15 papers · 1 filter
Steering Prediction via a Multi-Sensor System for Autonomous Racing
Zhuyun Zhou, Zongwei Wu, Florian Bolli +5
Autonomous racing has rapidly gained research attention. Traditionally, racing cars rely on 2D LiDAR as their primary visual system. In this work, we explore the integration of an…
Utility and Feasibility of a Center Surround Event Camera
Tobi Delbruck, Chenghan Li, Rui Graca +1
Standard dynamic vision sensor (DVS) event cameras output a stream of spatially-independent log-intensity brightness change events so they cannot suppress spatial redundancy. Nearl…
Bio-inspired Polarization Event Camera
Germain Haessig, Damien Joubert, Justin Haque +4
The stomatopod (mantis shrimp) visual system has recently provided a blueprint for the design of paradigm-shifting polarization and multispectral imaging sensors, enabling solution…
Feedback control of event cameras
Tobi Delbruck, Rui Graca, Marcin Paluch
Dynamic vision sensor event cameras produce a variable data rate stream of brightness change events. Event production at the pixel level is controlled by threshold, bandwidth, and…
v2e: From Video Frames to Realistic DVS Events
Yuhuang Hu, Shih-Chii Liu, Tobi Delbruck
To help meet the increasing need for dynamic vision sensor (DVS) event camera data, this paper proposes the v2e toolbox that generates realistic synthetic DVS events from intensity…
DDD20 End-to-End Event Camera Driving Dataset: Fusing Frames and Events with Deep Learning for Improved Steering Prediction
Yuhuang Hu, Jonathan Binas, Daniel Neil +2
Neuromorphic event cameras are useful for dynamic vision problems under difficult lighting conditions. To enable studies of using event cameras in automobile driving applications,…
Data-Driven Neuromorphic DRAM-based CNN and RNN Accelerators
Tobi Delbruck, Shih-Chii Liu
The energy consumed by running large deep neural networks (DNNs) on hardware accelerators is dominated by the need for lots of fast memory to store both states and weights. This la…
Learning to Exploit Multiple Vision Modalities by Using Grafted Networks
Yuhuang Hu, Tobi Delbruck, Shih-Chii Liu
Novel vision sensors such as thermal, hyperspectral, polarization, and event cameras provide information that is not available from conventional intensity cameras. An obstacle to u…
Dynamic Vision Sensor integration on FPGA-based CNN accelerators for high-speed visual classification
Alejandro Linares-Barranco, Antonio Rios-Navarro, Ricardo Tapiador-Morales +1
Deep-learning is a cutting edge theory that is being applied to many fields. For vision applications the Convolutional Neural Networks (CNN) are demanding significant accuracy for…
EV-IMO: Motion Segmentation Dataset and Learning Pipeline for Event Cameras
Anton Mitrokhin, Chengxi Ye, Cornelia Fermuller +2
We present the first event-based learning approach for motion segmentation in indoor scenes and the first event-based dataset - EV-IMO - which includes accurate pixel-wise motion m…
ABMOF: A Novel Optical Flow Algorithm for Dynamic Vision Sensors
Min Liu, Tobi Delbruck
Dynamic Vision Sensors (DVS), which output asynchronous log intensity change events, have potential applications in high-speed robotics, autonomous cars and drones. The precise eve…
DDD17: End-To-End DAVIS Driving Dataset
Jonathan Binas, Daniel Neil, Shih-Chii Liu +1
Event cameras, such as dynamic vision sensors (DVS), and dynamic and active-pixel vision sensors (DAVIS) can supplement other autonomous driving sensors by providing a concurrent s…
Block-Matching Optical Flow for Dynamic Vision Sensor- Algorithm and FPGA Implementation
Min Liu, Tobi Delbruck
Rapid and low power computation of optical flow (OF) is potentially useful in robotics. The dynamic vision sensor (DVS) event camera produces quick and sparse output, and has high…
NullHop: A Flexible Convolutional Neural Network Accelerator Based on Sparse Representations of Feature Maps
Alessandro Aimar, Hesham Mostafa, Enrico Calabrese +8
Convolutional neural networks (CNNs) have become the dominant neural network architecture for solving many state-of-the-art (SOA) visual processing tasks. Even though Graphical Pro…
Event-based, 6-DOF Camera Tracking from Photometric Depth Maps
Guillermo Gallego, Jon E. A. Lund, Elias Mueggler +3
Event cameras are bio-inspired vision sensors that output pixel-level brightness changes instead of standard intensity frames. These cameras do not suffer from motion blur and have…