Colour constancy using von Kries transformations: colour constancy "goes to the Lab"

Colour constancy algorithms aim at correcting colour towards a correct perception within scenes. To achieve this goal they estimate a white point (the illuminant's colour), and correct the scene for its in uence. In contrast, colour management performs on input images colour transformations according to a pre-established input pro le (ICC pro le) for the given con- stellation of input device (camera) and conditions (illumination situation). The latter case presents a much more analytic approach (it is not based on an estimation), and is based on solid colour science and current industry best practises, but it is rather in exible towards cases with altered conditions or capturing devices. The idea as outlined in this paper is to take up the idea of working on visually linearised and device independent CIE colour spaces as used in colour management, and to try to apply them in the eld of colour constancy. For this purpose two of the most well known colour constancy algorithms White Patch Retinex and Grey World Assumption have been ported to also work on colours in the CIE LAB colour space. Barnard's popular benchmarking set of imagery was corrected with the original imple- mentations as a reference and the modi ed algorithms. The results appeared to be promising, but they also revealed strengths and weaknesses

Benchmarking and Error Diagnosis in Multi-Instance Pose Estimation

We propose a new method to analyze the impact of errors in algorithms for multi-instance pose estimation and a principled benchmark that can be used to compare them. We define and characterize three classes of errors - localization, scoring, and background - study how they are influenced by instance attributes and their impact on an algorithm's performance. Our technique is applied to compare the two leading methods for human pose estimation on the COCO Dataset, measure the sensitivity of pose estimation with respect to instance size, type and number of visible keypoints, clutter due to multiple instances, and the relative score of instances. The performance of algorithms, and the types of error they make, are highly dependent on all these variables, but mostly on the number of keypoints and the clutter. The analysis and software tools we propose offer a novel and insightful approach for understanding the behavior of pose estimation algorithms and an effective method for measuring their strengths and weaknesses.Comment: Project page available at http://www.vision.caltech.edu/~mronchi/projects/PoseErrorDiagnosis/; Code available at https://github.com/matteorr/coco-analyze; published at ICCV 1

Dynamical Analysis of Nearby ClustErs. Automated astrometry from the ground: precision proper motions over wide field

The kinematic properties of the different classes of objects in a given association hold important clues about its member's history, and offer a unique opportunity to test the predictions of the various models of stellar formation and evolution. DANCe (standing for Dynamical Analysis of Nearby ClustErs) is a survey program aimed at deriving a comprehensive and homogeneous census of the stellar and substellar content of a number of nearby (<1kpc) young (<500Myr) associations. Whenever possible, members will be identified based on their kinematics properties, ensuring little contamination from background and foreground sources. Otherwise, the dynamics of previously confirmed members will be studied using the proper motion measurements. We present here the method used to derive precise proper motion measurements, using the Pleiades cluster as a test bench. Combining deep wide field multi-epoch panchromatic images obtained at various obervatories over up to 14 years, we derive accurate proper motions for the sources present in the field of the survey. The datasets cover ~80 square degrees, centered around the Seven Sisters. Using new tools, we have computed a catalog of 6116907 unique sources, including proper motion measurements for 3577478 of them. The catalogue covers the magnitude range between i=12~24mag, achieving a proper motion accuracy <1mas/yr for sources as faint as i=22.5mag. We estimate that our final accuracy reaches 0.3mas/yr in the best cases, depending on magnitude, observing history, and the presence of reference extragalactic sources for the anchoring onto the ICRS.Comment: Accepted for publication in A&

Visual sensor fusion for active security in robotic industrial environments

This work presents a method of information fusion involving data captured by both a standard CCD camera and a ToF camera to be used in the detection of the proximity between a manipulator robot and a human. Both cameras are assumed to be located above the work area of an industrial robot. The fusion of colour images and time of light information makes it possible to know the 3D localization of objects with respect to a world coordinate system. At the same time this allows to know their colour information. Considering that ToF information given by the range camera contains innacuracies including distance error, border error, and pixel saturation, some corrections over the ToF information are proposed and developed to improve the results. The proposed fusion method uses the calibration parameters of both cameras to reproject 3D ToF points, expressed in a common coordinate system for both cameras and a robot arm, in 2D colour images. In addition to this, using the 3D information, the motion detection in a robot industrial environment is achieved, and the fusion of information is applied to the foreground objects previously detected. This combination of information results in a matrix that links colour and 3D information, giving the possibility of characterising the object by its colour in addition to its 3D localization. Further development of these methods will make it possible to identify objects and their position in the real world, and to use this information to prevent possible collisions between the robot and such objects

Reconstructing Three-decade Global Fine-Grained Nighttime Light Observations by a New Super-Resolution Framework

Satellite-collected nighttime light provides a unique perspective on human activities, including urbanization, population growth, and epidemics. Yet, long-term and fine-grained nighttime light observations are lacking, leaving the analysis and applications of decades of light changes in urban facilities undeveloped. To fill this gap, we developed an innovative framework and used it to design a new super-resolution model that reconstructs low-resolution nighttime light data into high resolution. The validation of one billion data points shows that the correlation coefficient of our model at the global scale reaches 0.873, which is significantly higher than that of other existing models (maximum = 0.713). Our model also outperforms existing models at the national and urban scales. Furthermore, through an inspection of airports and roads, only our model's image details can reveal the historical development of these facilities. We provide the long-term and fine-grained nighttime light observations to promote research on human activities. The dataset is available at \url{https://doi.org/10.5281/zenodo.7859205}

Detection of the tulip breaking virus (TBV) in tulips using optical sensors

The tulip breaking virus (TBV) causes severe economic losses for countries that export tulips such as the Netherlands. Infected plants have to be removed from the field as soon as possible. There is an urgent need for a rapid and objective method of screening. In this study, four proximal optical sensing techniques for the detection of TBV in tulip plants were evaluated and compared with a visual assessment by crop experts as well as with an ELISA (enzyme immunoassay) analysis of the same plants. The optical sensor techniques used were an RGB color camera, a spectrophotometer measuring from 350 to 2500 nm, a spectral imaging camera covering a spectral range from 400 to 900 nm and a chlorophyll fluorescence imaging system that measures the photosynthetic activity. Linear discriminant classification was used to compare the results of these optical techniques and the visual assessment with the ELISA score. The spectral imaging system was the best optical technique and its error was only slightly larger than the visual assessment error. The experimental results appear to be promising, and they have led to further research to develop an autonomous robot for the detection and removal of diseased tulip plants in the open field. The application of this robot system will reduce the amount of insecticides and the considerable pressure on labor for selecting diseased plants by the crop expert. © 2010 The Author(s

The X-CLASS - redMaPPer galaxy cluster comparison: I. Identification procedures

We performed a detailed and, for a large part interactive, analysis of the matching output between the X-CLASS and redMaPPer cluster catalogues. The overlap between the two catalogues has been accurately determined and possible cluster positional errors were manually recovered. The final samples comprise 270 and 355 redMaPPer and X-CLASS clusters respectively. X-ray cluster matching rates were analysed as a function of optical richness. In a second step, the redMaPPer clusters were correlated with the entire X-ray catalogue, containing point and uncharacterised sources (down to a few 10^{-15} erg s^{-1} cm^{-2} in the [0.5-2] keV band). A stacking analysis was performed for the remaining undetected optical clusters. Main results show that neither of the wavebands misses any massive cluster (as coded by X-ray luminosity or optical richness). After correcting for obvious pipeline short-comings (about 10% of the cases both in optical and X-ray), ~50% of the redMaPPer (down to a richness of 20) are found to coincide with an X-CLASS cluster; when considering X-ray sources of any type, this fraction increases to ~ 80%; for the remaining objects, the stacking analysis finds a weak signal within 0.5 Mpc around the cluster optical centers. The fraction of clusters totally dominated by AGN-type emission appears to be of the order of a few percent. Conversely ~ 40% of the X-CLASS clusters are identified with a redMaPPer (down to a richness of 20) - part of the non-matches being due to the fact that the X-CLASS sample extends further out than redMaPPer (z<1 vs z<0.6); extending the correlation down to a richness of 5, raises the matching rate to ~ 65%.Comment: 15 pages, 20 figures, 2 table

Molecfit: A general tool for telluric absorption correction. I. Method and application to ESO instruments

Context: The interaction of the light from astronomical objects with the constituents of the Earth's atmosphere leads to the formation of telluric absorption lines in ground-based collected spectra. Correcting for these lines, mostly affecting the red and infrared region of the spectrum, usually relies on observations of specific stars obtained close in time and airmass to the science targets, therefore using precious observing time. Aims: We present molecfit, a tool for correcting for telluric absorption lines based on synthetic modelling of the Earth's atmospheric transmission. Molecfit is versatile and can be used with data obtained with various ground-based telescopes and instruments. Methods: Molecfit combines a publicly available radiative transfer code, a molecular line database, atmospheric profiles, and various kernels to model the instrument line spread function. The atmospheric profiles are created by merging a standard atmospheric profile representative of a given observatory's climate, of local meteorological data, and of dynamically retrieved altitude profiles for temperature, pressure, and humidity. We discuss the various ingredients of the method, its applicability, and its limitations. We also show examples of telluric line correction on spectra obtained with a suite of ESO Very Large Telescope (VLT) instruments. Results: Compared to previous similar tools, molecfit takes the best results for temperature, pressure, and humidity in the atmosphere above the observatory into account. As a result, the standard deviation of the residuals after correction of unsaturated telluric lines is frequently better than 2% of the continuum. Conclusion: Molecfit is able to accurately model and correct for telluric lines over a broad range of wavelengths and spectral resolutions. (Abridged)Comment: 18 pages, 13 figures, 5 tables, accepted for publication in Astronomy and Astrophysic