Characterization and mapping of surface physical properties of Mars from CRISM multi-angular data: application to Gusev Crater and Meridiani Planum

The analysis of the surface texture from the particle (grain size, shape and internal structure) to its organization (surface roughness) provides information on the geological processes. CRISM multi-angular observations (varied emission angles) allow to characterize the surface scattering behavior which depends on the composition but also the material physical properties (e.g., grain size, shape, internal structure, the surface roughness). After an atmospheric correction by the Multi-angle Approach for Retrieval of the Surface Reflectance from CRISM Observations, the surface reflectances at different geometries are analyzed by inverting the Hapke photometric model depending on the single scattering albedo, the 2-term phase function, the macroscopic roughness and the 2-term opposition effects. Surface photometric maps are created to observe the spatial variations of surface scattering properties as a function of geological units at the CRISM spatial resolution (200m/pixel). An application at the Mars Exploration Rover (MER) landing sites located at Gusev Crater and Meridiani Planum where orbital and in situ observations are available, is presented. Complementary orbital observations (e.g. CRISM spectra, THermal EMission Imaging System, High Resolution Imaging Science Experiment images) are used for interpreting the estimated Hapke photometric parameters in terms of physical properties. The in situ observations are used as ground truth to validate the interpretations. Varied scattering properties are observed inside a CRISM observation (5x10km) suggesting that the surfaces are controlled by local geological processes (e.g. volcanic resurfacing, aeolian and impact processes) rather than regional or global. Consistent results with the in situ observations are observed thus validating the approach and the use of photometry for the characterization of Martian surface physical properties

Overcoming the Challenges Associated with Image-based Mapping of Small Bodies in Preparation for the OSIRIS-REx Mission to (101955) Bennu

The OSIRIS-REx Asteroid Sample Return Mission is the third mission in NASA's New Frontiers Program and is the first U.S. mission to return samples from an asteroid to Earth. The most important decision ahead of the OSIRIS-REx team is the selection of a prime sample-site on the surface of asteroid (101955) Bennu. Mission success hinges on identifying a site that is safe and has regolith that can readily be ingested by the spacecraft's sampling mechanism. To inform this mission-critical decision, the surface of Bennu is mapped using the OSIRIS-REx Camera Suite and the images are used to develop several foundational data products. Acquiring the necessary inputs to these data products requires observational strategies that are defined specifically to overcome the challenges associated with mapping a small irregular body. We present these strategies in the context of assessing candidate sample-sites at Bennu according to a framework of decisions regarding the relative safety, sampleability, and scientific value across the asteroid's surface. To create data products that aid these assessments, we describe the best practices developed by the OSIRIS-REx team for image-based mapping of irregular small bodies. We emphasize the importance of using 3D shape models and the ability to work in body-fixed rectangular coordinates when dealing with planetary surfaces that cannot be uniquely addressed by body-fixed latitude and longitude.Comment: 31 pages, 10 figures, 2 table

A Decoupled 3D Facial Shape Model by Adversarial Training

Data-driven generative 3D face models are used to compactly encode facial shape data into meaningful parametric representations. A desirable property of these models is their ability to effectively decouple natural sources of variation, in particular identity and expression. While factorized representations have been proposed for that purpose, they are still limited in the variability they can capture and may present modeling artifacts when applied to tasks such as expression transfer. In this work, we explore a new direction with Generative Adversarial Networks and show that they contribute to better face modeling performances, especially in decoupling natural factors, while also achieving more diverse samples. To train the model we introduce a novel architecture that combines a 3D generator with a 2D discriminator that leverages conventional CNNs, where the two components are bridged by a geometry mapping layer. We further present a training scheme, based on auxiliary classifiers, to explicitly disentangle identity and expression attributes. Through quantitative and qualitative results on standard face datasets, we illustrate the benefits of our model and demonstrate that it outperforms competing state of the art methods in terms of decoupling and diversity.Comment: camera-ready version for ICCV'1

Multispectral RTI Analysis of Heterogeneous Artworks

We propose a novel multi-spectral reflectance transformation imaging (MS-RTI) framework for the acquisition and direct analysis of the reflectance behavior of heterogeneous artworks. Starting from free-form acquisitions, we compute per-pixel calibrated multi-spectral appearance profiles, which associate a reflectance value to each sampled light direction and frequency. Visualization, relighting, and feature extraction is performed directly on appearance profile data, applying scattered data interpolation based on Radial Basis Functions to estimate per-pixel reflectance from novel lighting directions. We demonstrate how the proposed solution can convey more insights on the object materials and geometric details compared to classical multi-light methods that rely on low-frequency analytical model fitting eventually mixed with a separate handling of high-frequency components, hence requiring constraining priors on material behavior. The flexibility of our approach is illustrated on two heterogeneous case studies, a painting and a dark shiny metallic sculpture, that showcase feature extraction, visualization, and analysis of high-frequency properties of artworks using multi-light, multi-spectral (Visible, UV and IR) acquisitions.Terms: "European Union (EU)" & "Horizon 2020" / Action: H2020-EU.3.6.3. - Reflective societies - cultural heritage and European identity / Acronym: Scan4Reco / Grant number: 665091the DSURF (PRIN 2015) project funded by the Italian Ministry of University and ResearchSardinian Regional Authorities under projects VIGEC and Vis&VideoLa

Surface reflectance of Mars observed by CRISM/MRO: 2. Estimation of surface photometric properties in Gusev Crater and Meridiani Planum

The present article proposes an approach to analyze the photometric properties of the surface materials from multi-angle observations acquired by the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) on-board the Mars Reconnaissance Orbiter. We estimate photometric parameters using Hapke model in a Bayesian inversion framework. This work also represents a validation of the atmospheric correction provided by the Multi-angle Approach for Retrieval of Surface Reflectance from CRISM Observations (MARS-ReCO) proposed in the companion article.The latter algorithm retrieves photometric curves of surface materials in reflectance units after removing the aerosol contribution. This validation is done by comparing the estimated photometric parameters to those obtained from in situ measurements by Panoramic Camera instrument at the Mars Exploration Rover (MER)-Spirit and MER-Opportunity landing sites. Consistent photometric parameters with those from in situ measurements are found, demonstrating that MARS-ReCO gives access to accurate surface reflectance. Moreover the assumption of a non-Lambertian surface as included in MARS-ReCO is shown to be significantly more precise to estimate surface photometric properties from space in comparison to methods based on a Lambertian surface assumption. In the future, the presented method will allow us to map from orbit the surface bidirectional reflectance and the related photometric parameters in order to characterize the Martian surface