Search Results for author:
Found 40 papers, 22 papers with code
Real-time Noise Source Estimation of a Camera System from an Image and Metadata
It also serves as a basis to include more advanced noise sources, or as part of an automatic countermeasure feedback-loop to approach fully reliable machines.
CMax-SLAM: Event-based Rotational-Motion Bundle Adjustment and SLAM System using Contrast Maximization
This paper considers the problem of rotational motion estimation using event cameras.
Low-power, Continuous Remote Behavioral Localization with Event Cameras
However, observing wild species at remote locations remains a challenging task due to difficult lighting conditions and constraints on power supply and data storage.
Event-based Continuous Color Video Decompression from Single Frames
We present ContinuityCam, a novel approach to generate a continuous video from a single static RGB image, using an event camera.
Event-based Background-Oriented Schlieren
Schlieren imaging is an optical technique to observe the flow of transparent media, such as air or water, without any particle seeding.
Fast Event-based Optical Flow Estimation by Triplet Matching
Event cameras are novel bio-inspired sensors that offer advantages over traditional cameras (low latency, high dynamic range, low power, etc.).
A Fast Geometric Regularizer to Mitigate Event Collapse in the Contrast Maximization Framework
We hope our work opens the door for future applications that unlocks the advantages of event cameras.
Event-based Stereo Depth Estimation from Ego-motion using Ray Density Fusion
Event cameras are bio-inspired sensors that mimic the human retina by responding to brightness changes in the scene.
Multi-Event-Camera Depth Estimation and Outlier Rejection by Refocused Events Fusion
Event cameras are bio-inspired sensors that offer advantages over traditional cameras.
Secrets of Event-Based Optical Flow
Event cameras respond to scene dynamics and offer advantages to estimate motion.
Stereo Co-capture System for Recording and Tracking Fish with Frame- and Event Cameras
This work introduces a co-capture system for multi-animal visual data acquisition using conventional cameras and event cameras.
Event Collapse in Contrast Maximization Frameworks
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.
Event-aided Direct Sparse Odometry
This opens the door to low-power motion-tracking applications where frames are sparingly triggered "on demand" and our method tracks the motion in between.
Formulating Event-based Image Reconstruction as a Linear Inverse Problem with Deep Regularization using Optical Flow
Event cameras are novel bio-inspired sensors that measure per-pixel brightness differences asynchronously.
Monitoring and Adapting the Physical State of a Camera for Autonomous Vehicles
Autonomous vehicles and robots require increasingly more robustness and reliability to meet the demands of modern tasks.
ESL: Event-based Structured Light
Event cameras are bio-inspired sensors providing significant advantages over standard cameras such as low latency, high temporal resolution, and high dynamic range.
Bounds, Heuristics, and Prophet Inequalities for Assortment Optimization
For the price-aware MNL, however, a clairvoyant firm can earn at most $\exp(1)$ more than a traditional firm.
The Spatio-Temporal Poisson Point Process: A Simple Model for the Alignment of Event Camera Data
In particular, we model the aligned data as a spatio-temporal Poisson point process.
The Refined Assortment Optimization Problem
We introduce the refined assortment optimization problem where a firm may decide to make some of its products harder to get instead of making them unavailable as in the traditional assortment optimization problem.
Bounds and Heuristics for Multi-Product Personalized Pricing
Numerical results are presented for a variety of demand models that illustrate the tradeoffs between using the economic factor and the robust factor for each cluster, as well as the tradeoffs between using a clustering heuristic with a worst case performance of two and a machine learning clustering algorithm.
Event-based Motion Segmentation with Spatio-Temporal Graph Cuts
We develop a method to identify independently moving objects acquired with an event-based camera, i. e., to solve the event-based motion segmentation problem.
Event-based Stereo Visual Odometry
We present a solution to the problem of visual odometry from the data acquired by a stereo event-based camera rig.
The Use of Binary Choice Forests to Model and Estimate Discrete Choices
We also prove that the random forest can recover preference rankings of customers thanks to the splitting criterion such as the Gini index and information gain ratio.
Event-based Vision: A Survey
Event cameras offer attractive properties compared to traditional cameras: high temporal resolution (in the order of microseconds), very high dynamic range (140 dB vs. 60 dB), low power consumption, and high pixel bandwidth (on the order of kHz) resulting in reduced motion blur.
Focus Is All You Need: Loss Functions For Event-based Vision
The proposed loss functions allow bringing mature computer vision tools to the realm of event cameras.
Event-Based Motion Segmentation by Motion Compensation
In contrast to traditional cameras, whose pixels have a common exposure time, event-based cameras are novel bio-inspired sensors whose pixels work independently and asynchronously output intensity changes (called "events"), with microsecond resolution.
A Primal-dual Learning Algorithm for Personalized Dynamic Pricing with an Inventory Constraint
We consider the problem of a firm seeking to use personalized pricing to sell an exogenously given stock of a product over a finite selling horizon to different consumer types.
Asynchronous, Photometric Feature Tracking using Events and Frames
By contrast, standard cameras provide intensity measurements (frames) that do not depend on motion direction.
Semi-Dense 3D Reconstruction with a Stereo Event Camera
Event cameras are bio-inspired sensors that offer several advantages, such as low latency, high-speed and high dynamic range, to tackle challenging scenarios in computer vision.
Nonparametric Pricing Analytics with Customer Covariates
We propose a nonparametric pricing policy to simultaneously learn the preference of customers based on the covariates and maximize the expected revenue over a finite horizon.
A Unifying Contrast Maximization Framework for Event Cameras, with Applications to Motion, Depth, and Optical Flow Estimation
We present a unifying framework to solve several computer vision problems with event cameras: motion, depth and optical flow estimation.
Event-based Vision meets Deep Learning on Steering Prediction for Self-driving Cars
Event cameras are bio-inspired vision sensors that naturally capture the dynamics of a scene, filtering out redundant information.
Ranked #12 on
Robust classification
on N-ImageNet
Translation of "Zur Ermittlung eines Objektes aus zwei Perspektiven mit innerer Orientierung" by Erwin Kruppa (1913)
1939-1948, which may be translated as "To determine a 3D object from two perspective views with known inner orientation", is a landmark paper in Computer Vision because it provides the first five-point algorithm for relative pose estimation.
Continuous-Time Visual-Inertial Odometry for Event Cameras
Recent work has shown that a continuous-time representation of the event camera pose can deal with the high temporal resolution and asynchronous nature of this sensor in a principled way.
The Event-Camera Dataset and Simulator: Event-based Data for Pose Estimation, Visual Odometry, and SLAM
New vision sensors, such as the Dynamic and Active-pixel Vision sensor (DAVIS), incorporate a conventional global-shutter camera and an event-based sensor in the same pixel array.
Event-based, 6-DOF Camera Tracking from Photometric Depth Maps
Event cameras are bio-inspired vision sensors that output pixel-level brightness changes instead of standard intensity frames.
Optimal Piecewise Linear Function Approximation for GPU-based Applications
The proposed technique is a perfect match for any application requiring the evaluation of continuous functions, we have measured in detail its quality and efficiency on several functions, and, in particular, the Gaussian function because it is extensively used in many areas of computer vision and cybernetics, and it is expensive to evaluate.
Event-based Camera Pose Tracking using a Generative Event Model
Event-based vision sensors mimic the operation of biological retina and they represent a major paradigm shift from traditional cameras.
A compact formula for the derivative of a 3-D rotation in exponential coordinates
We present a compact formula for the derivative of a 3-D rotation matrix with respect to its exponential coordinates.
Autocalibration with the Minimum Number of Cameras with Known Pixel Shape
In the absence of information about the internal camera parameters such as the focal length and the principal point, the knowledge of the camera pixel shape is usually the only available constraint.
