2.3k citations · 5.9k across the 43 of their papers we have counts for
43 papers
Fourier-based Action Recognition for Wildlife Behavior Quantification with Event Cameras
Friedhelm Hamann, Suman Ghosh, Ignacio Juarez Martinez +3
Event cameras are novel bio-inspired vision sensors that measure pixel-wise brightness changes asynchronously instead of images at a given frame rate. They offer promising advantag…
Event-based Mosaicing Bundle Adjustment
Shuang Guo, Guillermo Gallego
We tackle the problem of mosaicing bundle adjustment (i.e., simultaneous refinement of camera orientations and scene map) for a purely rotating event camera. We formulate the probl…
Event-based Stereo Depth Estimation: A Survey
Suman Ghosh, Guillermo Gallego
Stereopsis has widespread appeal in robotics as it is the predominant way by which living beings perceive depth to navigate our 3D world. Event cameras are novel bio-inspired senso…
ES-PTAM: Event-based Stereo Parallel Tracking and Mapping
Suman Ghosh, Valentina Cavinato, Guillermo Gallego
Visual Odometry (VO) and SLAM are fundamental components for spatial perception in mobile robots. Despite enormous progress in the field, current VO/SLAM systems are limited by the…
On the Benefits of Visual Stabilization for Frame- and Event-based Perception
Juan Pablo Rodriguez-Gomez, Jose Ramiro Martinez-de Dios, Anibal Ollero +1
Vision-based perception systems are typically exposed to large orientation changes in different robot applications. In such conditions, their performance might be compromised due t…
Motion-prior Contrast Maximization for Dense Continuous-Time Motion Estimation
Friedhelm Hamann, Ziyun Wang, Ioannis Asmanis +3
Current optical flow and point-tracking methods rely heavily on synthetic datasets. Event cameras are novel vision sensors with advantages in challenging visual conditions, but sta…
Motion and Structure from Event-based Normal Flow
Zhongyang Ren, Bangyan Liao, Delei Kong +5
Recovering the camera motion and scene geometry from visual data is a fundamental problem in the field of computer vision. Its success in standard vision is attributed to the matur…
Real-time Noise Source Estimation of a Camera System from an Image and Metadata
Maik Wischow, Patrick Irmisch, Anko Boerner +1
Autonomous machines must self-maintain proper functionality to ensure the safety of humans and themselves. This pertains particularly to its cameras as predominant sensors to perce…
CMax-SLAM: Event-based Rotational-Motion Bundle Adjustment and SLAM System using Contrast Maximization
Shuang Guo, Guillermo Gallego
Event cameras are bio-inspired visual sensors that capture pixel-wise intensity changes and output asynchronous event streams. They show great potential over conventional cameras t…
Low-power, Continuous Remote Behavioral Localization with Event Cameras
Friedhelm Hamann, Suman Ghosh, Ignacio Juarez Martinez +3
Researchers in natural science need reliable methods for quantifying animal behavior. Recently, numerous computer vision methods emerged to automate the process. However, observing…
Event-based Continuous Color Video Decompression from Single Frames
Ziyun Wang, Friedhelm Hamann, Kenneth Chaney +3
We present ContinuityCam, a novel approach to generate a continuous video from a single static RGB image and an event camera stream. Conventional cameras struggle with high-speed m…
Event-based Background-Oriented Schlieren
Shintaro Shiba, Friedhelm Hamann, Yoshimitsu Aoki +1
Schlieren imaging is an optical technique to observe the flow of transparent media, such as air or water, without any particle seeding. However, conventional frame-based techniques…
Fast Event-based Optical Flow Estimation by Triplet Matching
Shintaro Shiba, Yoshimitsu Aoki, Guillermo Gallego
Event cameras are novel bio-inspired sensors that offer advantages over traditional cameras (low latency, high dynamic range, low power, etc.). Optical flow estimation methods that…
A Fast Geometric Regularizer to Mitigate Event Collapse in the Contrast Maximization Framework
Shintaro Shiba, Yoshimitsu Aoki, Guillermo Gallego
Event cameras are emerging vision sensors and their advantages are suitable for various applications such as autonomous robots. Contrast maximization (CMax), which provides state-o…
Event-based Stereo Depth Estimation from Ego-motion using Ray Density Fusion
Suman Ghosh, Guillermo Gallego
Event cameras are bio-inspired sensors that mimic the human retina by responding to brightness changes in the scene. They generate asynchronous spike-based outputs at microsecond r…
Secrets of Event-Based Optical Flow
Shintaro Shiba, Yoshimitsu Aoki, Guillermo Gallego
Event cameras respond to scene dynamics and offer advantages to estimate motion. Following recent image-based deep-learning achievements, optical flow estimation methods for event…
Event Collapse in Contrast Maximization Frameworks
Shintaro Shiba, Yoshimitsu Aoki, Guillermo Gallego
Contrast maximization (CMax) is a framework that provides state-of-the-art results on several event-based computer vision tasks, such as ego-motion or optical flow estimation. Howe…
Multi-Event-Camera Depth Estimation and Outlier Rejection by Refocused Events Fusion
Suman Ghosh, Guillermo Gallego
Event cameras are bio-inspired sensors that offer advantages over traditional cameras. They operate asynchronously, sampling the scene at microsecond resolution and producing a str…
Stereo Co-capture System for Recording and Tracking Fish with Frame- and Event Cameras
Friedhelm Hamann, Guillermo Gallego
This work introduces a co-capture system for multi-animal visual data acquisition using conventional cameras and event cameras. Event cameras offer multiple advantages over frame-b…
Event-aided Direct Sparse Odometry
Javier Hidalgo-Carrió, Guillermo Gallego, Davide Scaramuzza
We introduce EDS, a direct monocular visual odometry using events and frames. Our algorithm leverages the event generation model to track the camera motion in the blind time betwee…
Formulating Event-based Image Reconstruction as a Linear Inverse Problem with Deep Regularization using Optical Flow
Zelin Zhang, Anthony Yezzi, Guillermo Gallego
Event cameras are novel bio-inspired sensors that measure per-pixel brightness differences asynchronously. Recovering brightness from events is appealing since the reconstructed im…
Monitoring and Adapting the Physical State of a Camera for Autonomous Vehicles
Maik Wischow, Guillermo Gallego, Ines Ernst +1
Autonomous vehicles and robots require increasingly more robustness and reliability to meet the demands of modern tasks. These requirements specially apply to cameras onboard such…
ESL: Event-based Structured Light
Manasi Muglikar, Guillermo Gallego, Davide Scaramuzza
Event cameras are bio-inspired sensors providing significant advantages over standard cameras such as low latency, high temporal resolution, and high dynamic range. We propose a no…
The Spatio-Temporal Poisson Point Process: A Simple Model for the Alignment of Event Camera Data
Cheng Gu, Erik Learned-Miller, Daniel Sheldon +2
Event cameras, inspired by biological vision systems, provide a natural and data efficient representation of visual information. Visual information is acquired in the form of event…