Photometric reconstruction of a dynamic textured surface from just one color image acquisition

http://www.opticsinfobase.org/josaa/abstract.cfm?msid=85528 This article has been selected for inclusion in the Virtual Journal for Biomedical Optics (Vol. 3, Iss. 4)International audienceTextured surface analysis is essential for many applications. We present a three-dimensional recovery approach for real textured surfaces based on photometric stereo. The aim is to be able to measure the textured surfaces with a high degree of accuracy. For this, we use a color digital sensor and principles of color photometric stereo. This method uses a single color image, instead of a sequence of gray-scale images, to recover the surface of the three dimensions. It can thus be integrated into dynamic systems where there is significant relative motion between the object and the camera. To evaluate the performances of our method, we compare it on real textured surfaces to traditional photometric stereo using three images. We show thus that it is possible to have similar results with just one color image

3-D Motion Estimation and Wireframe Adaptation Including Photometric Effects for Model-Based Coding of Facial Image Sequences

Cataloged from PDF version of article.We propose a novel formulation where 3-D global and local motion estimation and the adaptation of a generic wireframe model to a particular speaker are considered simultaneously within an optical flow based framework including the photometric effects of the motion. We use a flexible wireframe model whose local structure is characterized by the normal vectors of the patches which are related to the coordinates of the nodes. Geometrical constraints that describe the propagation of the movement of the nodes are introduced, which are then efficiently utilized to reduce the number of independent structure parameters. A stochastic relaxation algorithm has been used to determine optimum global motion estimates and the parameters describing the structure of the wireframe model. Results with both simulated and real facial image sequences are provided

Simultaneous 3-D motion estimation and wire-frame model adaptation including photometric effects for knowledge-based video coding

We address the problem of 3-D motion estimation in the context of knowledge-based coding of facial image sequences. The proposed method handles the global and local motion estimation and the adaptation of a generic wire-frame to a particular speaker simultaneously within an optical flow based framework including the photometric effects of motion. We use a flexible wire-frame model whose local structure is characterized by the normal vectors of the patches which are related to the coordinates of the nodes. Geometrical constraints that describe the propagation of the movement of the nodes are introduced, which are then efficiently utilized to reduce the number of independent structure parameters. A stochastic relaxation algorithm has been used to determine optimum global motion estimates and the parameters describing the structure of the wire-frame model. For the initialization of the motion and structure parameters, a modified feature based algorithm is used. Experimental results with simulated facial image sequences are given. © 1994 IEEE

Identification of the top TESS objects of interest for atmospheric characterization of transiting exoplanets with JWST

Funding: Funding for the TESS mission is provided by NASA's Science Mission Directorate. This work makes use of observations from the LCOGT network. Part of the LCOGT telescope time was granted by NOIRLab through the Mid-Scale Innovations Program (MSIP). MSIP is funded by NSF. This paper is based on observations made with the MuSCAT3 instrument, developed by the Astrobiology Center and under financial support by JSPS KAKENHI (grant No. JP18H05439) and JST PRESTO (grant No. JPMJPR1775), at Faulkes Telescope North on Maui, HI, operated by the Las Cumbres Observatory. This paper makes use of data from the MEarth Project, which is a collaboration between Harvard University and the Smithsonian Astrophysical Observatory. The MEarth Project acknowledges funding from the David and Lucile Packard Fellowship for Science and Engineering, the National Science Foundation under grant Nos. AST-0807690, AST-1109468, AST-1616624 and AST-1004488 (Alan T. Waterman Award), the National Aeronautics and Space Administration under grant No. 80NSSC18K0476 issued through the XRP Program, and the John Templeton Foundation. C.M. would like to gratefully acknowledge the entire Dragonfly Telephoto Array team, and Bob Abraham in particular, for allowing their telescope bright time to be put to use observing exoplanets. B.J.H. acknowledges support from the Future Investigators in NASA Earth and Space Science and Technology (FINESST) program (grant No. 80NSSC20K1551) and support by NASA under grant No. 80GSFC21M0002. K.A.C. and C.N.W. acknowledge support from the TESS mission via subaward s3449 from MIT. D.R.C. and C.A.C. acknowledge support from NASA through the XRP grant No. 18-2XRP18_2-0007. C.A.C. acknowledges that this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004). S.Z. and A.B. acknowledge support from the Israel Ministry of Science and Technology (grant No. 3-18143). The research leading to these results has received funding from the ARC grant for Concerted Research Actions, financed by the Wallonia-Brussels Federation. TRAPPIST is funded by the Belgian Fund for Scientific Research (Fond National de la Recherche Scientifique, FNRS) under the grant No. PDR T.0120.21. The postdoctoral fellowship of K.B. is funded by F.R.S.-FNRS grant No. T.0109.20 and by the Francqui Foundation. H.P.O.'s contribution has been carried out within the framework of the NCCR PlanetS supported by the Swiss National Science Foundation under grant Nos. 51NF40_182901 and 51NF40_205606. F.J.P. acknowledges financial support from the grant No. CEX2021-001131-S funded by MCIN/AEI/ 10.13039/501100011033. A.J. acknowledges support from ANID—Millennium Science Initiative—ICN12_009 and from FONDECYT project 1210718. Z.L.D. acknowledges the MIT Presidential Fellowship and that this material is based upon work supported by the National Science Foundation Graduate Research Fellowship under grant No. 1745302. P.R. acknowledges support from the National Science Foundation grant No. 1952545. This work is partly supported by JSPS KAKENHI grant Nos. JP17H04574, JP18H05439, JP21K20376; JST CREST grant No. JPMJCR1761; and Astrobiology Center SATELLITE Research project AB022006. This publication benefits from the support of the French Community of Belgium in the context of the FRIA Doctoral Grant awarded to M.T. D.D. acknowledges support from TESS Guest Investigator Program grant Nos. 80NSSC22K1353, 80NSSC22K0185, and 80NSSC23K0769. A.B. acknowledges the support of M.V. Lomonosov Moscow State University Program of Development. T.D. was supported in part by the McDonnell Center for the Space Sciences. V.K. acknowledges support from the youth scientific laboratory project, topic FEUZ-2020-0038.JWST has ushered in an era of unprecedented ability to characterize exoplanetary atmospheres. While there are over 5000 confirmed planets, more than 4000 Transiting Exoplanet Survey Satellite (TESS) planet candidates are still unconfirmed and many of the best planets for atmospheric characterization may remain to be identified. We present a sample of TESS planets and planet candidates that we identify as “best-in-class” for transmission and emission spectroscopy with JWST. These targets are sorted into bins across equilibrium temperature Teq and planetary radius Rp and are ranked by a transmission and an emission spectroscopy metric (TSM and ESM, respectively) within each bin. We perform cuts for expected signal size and stellar brightness to remove suboptimal targets for JWST. Of the 194 targets in the resulting sample, 103 are unconfirmed TESS planet candidates, also known as TESS Objects of Interest (TOIs). We perform vetting and statistical validation analyses on these 103 targets to determine which are likely planets and which are likely false positives, incorporating ground-based follow-up from the TESS Follow-up Observation Program to aid the vetting and validation process. We statistically validate 18 TOIs, marginally validate 31 TOIs to varying levels of confidence, deem 29 TOIs likely false positives, and leave the dispositions for four TOIs as inconclusive. Twenty-one of the 103 TOIs were confirmed independently over the course of our analysis. We intend for this work to serve as a community resource and motivate formal confirmation and mass measurements of each validated planet. We encourage more detailed analysis of individual targets by the community.Peer reviewe

Not that they in or lose, but how you watch the game : personalized sports viewing

Thesis (M.S.)--Massachusetts Institute of Technology, Program in Media Arts & Sciences, 1994.Includes bibliographical references (leaves 117-127).by M. Cristina Dolan, Jr.M.S