Cloud base height estimates from sky imagery and a network of pyranometers

Cloud base height (CBH) is an important parameter for physics-based high resolution solar radiation modeling. In sky imager-based forecasts, a ceilometer or stereographic setup is needed to derive the CBH; otherwise erroneous CBHs lead to incorrect physical cloud velocity and incorrect projection of cloud shadows, causing solar power forecast errors due to incorrect shadow positions and timing of shadowing events. In this paper, two methods to estimate cloud base height from a single sky imager and distributed ground solar irradiance measurements are proposed. The first method (Time Series Correlation, denoted as “TSC”) is based upon the correlation between ground-observed global horizontal irradiance (GHI) time series and a modeled GHI time series generated from a sequence of sky images geo-rectified to a candidate set of CBH. The estimated CBH is taken as the candidate that produces the highest correlation coefficient. The second method (Geometric Cloud Shadow Edge, denoted as “GCSE”) integrates a numerical ramp detection method for ground-observed GHI time series with solar and cloud geometry applied to cloud edges in a sky image. CBH are benchmarked against a collocated ceilometer and stereographically estimated CBH from two sky imagers for 15 min median-filtered CBHs. Over 30 days covering all seasons, the TSC method performs similarly to the GCSE method with nRMSD of 18.9% versus 20.8%. A key limitation of both proposed methods is the requirement of sufficient variation in GHI to enable reliable correlation and ramp detection. The advantage of the two proposed methods is that they can be applied when measurements from only a single sky imager and pyranometers are available

Robust Temporally Coherent Laplacian Protrusion Segmentation of 3D Articulated Bodies

In motion analysis and understanding it is important to be able to fit a suitable model or structure to the temporal series of observed data, in order to describe motion patterns in a compact way, and to discriminate between them. In an unsupervised context, i.e., no prior model of the moving object(s) is available, such a structure has to be learned from the data in a bottom-up fashion. In recent times, volumetric approaches in which the motion is captured from a number of cameras and a voxel-set representation of the body is built from the camera views, have gained ground due to attractive features such as inherent view-invariance and robustness to occlusions. Automatic, unsupervised segmentation of moving bodies along entire sequences, in a temporally-coherent and robust way, has the potential to provide a means of constructing a bottom-up model of the moving body, and track motion cues that may be later exploited for motion classification. Spectral methods such as locally linear embedding (LLE) can be useful in this context, as they preserve "protrusions", i.e., high-curvature regions of the 3D volume, of articulated shapes, while improving their separation in a lower dimensional space, making them in this way easier to cluster. In this paper we therefore propose a spectral approach to unsupervised and temporally-coherent body-protrusion segmentation along time sequences. Volumetric shapes are clustered in an embedding space, clusters are propagated in time to ensure coherence, and merged or split to accommodate changes in the body's topology. Experiments on both synthetic and real sequences of dense voxel-set data are shown. This supports the ability of the proposed method to cluster body-parts consistently over time in a totally unsupervised fashion, its robustness to sampling density and shape quality, and its potential for bottom-up model constructionComment: 31 pages, 26 figure

Phase light curves for extrasolar Jupiters and Saturns

We predict how a remote observer would see the brightness variations of giant planets similar to Jupiter and Saturn as they orbit their central stars. We model the geometry of Jupiter, Saturn and Saturn's rings for varying orbital and viewing parameters. Scattering properties for the planets and rings at wavelenghts 0.6-0.7 microns follow Pioneer and Voyager observations, namely, planets are forward scattering and rings are backward scattering. Images of the planet with or without rings are simulated and used to calculate the disk-averaged luminosity varying along the orbit, that is, a light curve is generated. We find that the different scattering properties of Jupiter and Saturn (without rings) make a substantial difference in the shape of their light curves. Saturn-size rings increase the apparent luminosity of the planet by a factor of 2-3 for a wide range of geometries. Rings produce asymmetric light curves that are distinct from the light curve of the planet without rings. If radial velocity data are available for the planet, the effect of the ring on the light curve can be distinguished from effects due to orbital eccentricity. Non-ringed planets on eccentric orbits produce light curves with maxima shifted relative to the position of the maximum planet's phase. Given radial velocity data, the amount of the shift restricts the planet's unknown orbital inclination and therefore its mass. Combination of radial velocity data and a light curve for a non-ringed planet on an eccentric orbit can also be used to constrain the surface scattering properties of the planet. To summarize our results for the detectability of exoplanets in reflected light, we present a chart of light curve amplitudes of non-ringed planets for different eccentricities, inclinations, and the viewing azimuthal angles of the observer.Comment: 40 pages, 13 figures, submitted to Ap.