Correction to: EKLT: Asynchronous Photometric Feature Tracking Using Events and Frames

International Journal of Computer Vision - The original version of this article was unfortunately omitted to publish the footnote “The best result per row is highlighted in bold” in...     

Landsat-7 ETM+ on-orbit reflective-band radiometric stability and absolute calibration

Launched in April 1999, the Landsat-7 Enhanced Thematic Mapper Plus (ETM+) instrument is in its sixth year of operation. The ETM+ instrument has been the most stable of any of the Landsat instruments. To date, the best onboard calibration source for the reflective bands has been the Full Aperture Solar Calibrator, a solar-diffuser-based system, which has indicated changes of between 1% to 2% per year in the ETM+ gain for bands 1-4 and 8 and less than 0.5%/year for bands 5 and 7. However, most of this change is believed to be caused by changes in the solar diffuser panel, as opposed to a change in the instrument's gain. This belief is based partially on vicarious calibrations and observations of "invariant sites", hyperarid sites of the Sahara and Arabia. Weighted average slopes determined from these datasets suggest changes of 0.0% to 0.4% per year for bands 1-4 and 8 and 0.4% to 0.5% per year for bands 5 and 7. Absolute calibration of the reflective bands of the ETM+ is consistent with vicarious observations and other sensors generally at the 5% level, though there appear to be some systematic differences.     

Air‐ground Matching: Appearance‐based GPS‐denied Urban Localization of Micro Aerial Vehicles

In this paper, we address the problem of globally localizing and tracking the pose of a camera‐equipped micro aerial vehicle (MAV) flying in urban streets at low altitudes without GPS. An image‐based global positioning system is introduced to localize the MAV with respect to the surrounding buildings. We propose a novel air‐ground image‐matching algorithm to search the airborne image of the MAV within a ground‐level, geotagged image database. Based on the detected matching image features, we infer the global position of the MAV by back‐projecting the corresponding image points onto a cadastral three‐dimensional city model. Furthermore, we describe an algorithm to track the position of the flying vehicle over several frames and to correct the accumulated drift of the visual odometry whenever a good match is detected between the airborne and the ground‐level images. The proposed approach is tested on a 2 km trajectory with a small quadrocopter flying in the streets of Zurich. Our vision‐based global localization can robustly handle extreme changes in viewpoint, illumination, perceptual aliasing, and over‐season variations, thus outperforming conventional visual place‐recognition approaches. The dataset is made publicly available to the research community. To the best of our knowledge, this is the first work that studies and demonstrates global localization and position tracking of a drone in urban streets with a single onboard camera.     

AlphaPilot: autonomous drone racing

Autonomous Robots - This paper presents a novel system for autonomous, vision-based drone racing combining learned data abstraction, nonlinear filtering, and time-optimal trajectory planning. The...     

Optical and electrical characterization of a gold nanoparticle dispersion in a chiral liquid crystal matrix

We report on the effect of gold nanoparticle (Au NP) dispersion in a chiral nematic liquid crystal (LC). Polarized optical microscopy and X-ray diffraction measurements evidence the insurgence of an order change in the LC host. Moreover, a comparative analysis based on dielectric and voltammetric spectroscopies performed on pure LC and on Au NP-doped LC shows that Au NP’s presence besides affecting LC order influences its electric properties: ion conductivity results importantly reduced, and beyond a threshold value of the applied field electrophoresis phenomena are induced.     

The current state and future outlook of rescue robotics

Robotic technologies, whether they are remotely operated vehicles, autonomous agents, assistive devices, or novel control interfaces, offer many promising capabilities for deployment in real‐world environments. Postdisaster scenarios are a particularly relevant target for applying such technologies, due to the challenging conditions faced by rescue workers and the possibility to increase their efficacy while decreasing the risks they face. However, field‐deployable technologies for rescue work have requirements for robustness, speed, versatility, and ease of use that may not be matched by the state of the art in robotics research. This paper aims to survey the current state of the art in ground and aerial robots, marine and amphibious systems, and human–robot control interfaces and assess the readiness of these technologies with respect to the needs of first responders and disaster recovery efforts. We have gathered expert opinions from emergency response stakeholders and researchers who conduct field deployments with them to understand these needs, and we present this assessment as a way to guide future research toward technologies that will make an impact in real‐world disaster response and recovery.     

A comparison of volumetric information gain metrics for active 3D object reconstruction

In this paper, we investigate the following question: when performing next best view selection for volumetric 3D reconstruction of an object by a mobile robot equipped with a dense (camera-based) depth sensor, what formulation of information gain is best? To address this question, we propose several new ways to quantify the volumetric information (VI) contained in the voxels of a probabilistic volumetric map, and compare them to the state of the art with extensive simulated experiments. Our proposed formulations incorporate factors such as visibility likelihood and the likelihood of seeing new parts of the object. The results of our experiments allow us to draw some clear conclusions about the VI formulations that are most effective in different mobile-robot reconstruction scenarios. To the best of our knowledge, this is the first comparative survey of VI formulation performance for active 3D object reconstruction. Additionally, our modular software framework is adaptable to other robotic platforms and general reconstruction problems, and we release it open source for autonomous reconstruction tasks.     

Evaluation and Comparison of the IRS-P6 and the Landsat Sensors

The Indian Remote Sensing Satellite (IRS-P6), also called ResourceSat-1, was launched in a polar sun-synchronous orbit on October 17, 2003. It carries three sensors: the high-resolution Linear Imaging Self-Scanner (LISS-IV), the medium-resolution Linear Imaging Self-Scanner (LISS-III), and the Advanced Wide-Field Sensor (AWiFS). These three sensors provide images of different resolutions and coverage. To understand the absolute radiometric calibration accuracy of IRS-P6 AWiFS and LISS-III sensors, image pairs from these sensors were compared to images from the Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced TM Plus (ETM+) sensors. The approach involves calibration of surface observations based on image statistics from areas observed nearly simultaneously by the two sensors. This paper also evaluated the viability of data from these next-generation imagers for use in creating three National Land Cover Dataset (NLCD) products: land cover, percent tree canopy, and percent impervious surface. Individual products were consistent with previous studies but had slightly lower overall accuracies as compared to data from the Landsat sensors.     

EKLT: Asynchronous Photometric Feature Tracking Using Events and Frames

International Journal of Computer Vision - We present EKLT, a feature tracking method that leverages the complementarity of event cameras and standard cameras to track visual features with high...