{"title":"Parameter estimation of a reflection model from a multi-band image","authors":"S. Tominaga, E. Takahashi, N. Tanaka","doi":"10.1109/PMCVG.1999.787762","DOIUrl":"https://doi.org/10.1109/PMCVG.1999.787762","url":null,"abstract":"The present paper proposes a method for estimating various parameters of a reflection model from a single image of an object taken by a multi-band CCD camera. It is assumed that the object's surface is composed of an inhomogeneous dielectric material and has the shape of a cylinder. The Phong model is used as the three-dimensional reflection model, and a six-color camera is used as the multi-band CCD camera. We show some features of the reflection model and the image histogram. The model parameters to be estimated are such parameters as (1) surface-spectral reflectance, (2) illuminant spectral distribution, (3) illumination direction, (4) specular reflection exponent, and (5) ratio of body to interface intensity. The reflection parameters are estimated by analyzing the histogram on the color signal plane and making a relationship between the histogram features and the spatial points. The feasibility of the proposed method is demonstrated in an experiment using a plastic object. Computer graphics images are produced on the estimated model.","PeriodicalId":309370,"journal":{"name":"Proceedings Workshop on Photometric Modeling for Computer Vision and Graphics (Cat. No.PR00271)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121002024","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Color correction using explicit illumination models, color and registered range","authors":"M. W. Powell, S. Sarkar, D. Goldgof","doi":"10.1109/PMCVG.1999.787763","DOIUrl":"https://doi.org/10.1109/PMCVG.1999.787763","url":null,"abstract":"This work focuses on correcting color images illuminated by one or more light sources to improve the results of segmentation and feature extraction. First, we linearize the RGB data to make it conform to the assumptions made by many image processing algorithms. Then, we also eliminate intensity variation due to the illuminant with respect to distance and shading produced by surface orientation changes. We introduce a novel calibration procedure for estimating the finite distance and direction of the light source from points in the scene. We compare segmentations of original color images with that of their color-corrected images to evaluate the effectiveness of the methodology.","PeriodicalId":309370,"journal":{"name":"Proceedings Workshop on Photometric Modeling for Computer Vision and Graphics (Cat. No.PR00271)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122547245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Physics based modeling and rendering of vegetation in the thermal infrared","authors":"J.A. Smith, J.R. Ballard","doi":"10.1109/PMCVG.1999.787759","DOIUrl":"https://doi.org/10.1109/PMCVG.1999.787759","url":null,"abstract":"We outline a procedure for rendering physically-based thermal infrared images of simple vegetation scenes. Our approach incorporates the biophysical processes that affect the temperature distribution of the elements within a scene. Computer graphics plays a key role in two respects. First, in computing the distribution of scene shaded and sunlit facets and, second, in the final image rendering once the temperatures of all the elements in the scene have been computed. We illustrate our approach for a simple corn scene where the three-dimensional geometry is constructed based on measured morphological attributes of the row crop. Statistical methods are used to construct a representation of the scene in agreement with the measured characteristics. Our results are quite good. The rendered images exhibit realistic behavior in directional properties as a function of view and sun angle. The root-mean-square error in measured versus predicted brightness temperatures for the scene was 2.1 deg C.","PeriodicalId":309370,"journal":{"name":"Proceedings Workshop on Photometric Modeling for Computer Vision and Graphics (Cat. No.PR00271)","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124866586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Gaussian curvature from photometric scatter plots","authors":"E. Angelopoulou","doi":"10.1109/PMCVG.1999.787757","DOIUrl":"https://doi.org/10.1109/PMCVG.1999.787757","url":null,"abstract":"Local surface curvature is an important shape descriptor, especially for smooth featureless objects. For this family of objects, if their surface is matte, there is a one-to-one mapping between their surface normal map and the photometric data collected from a scene under three different illumination conditions. This mapping allows for the extraction of the sign and the magnitude of Gaussian curvature (to within a constant multiple) directly from intensity values. Because all the computations are performed in photometric space, the normal map is never recovered. This implies that the precise location of the light sources is not needed for any of the computations. Experiments show that a simple setup with minimal illumination planning and calibration is sufficient for the extraction of Gaussian curvature for smooth diffuse surfaces.","PeriodicalId":309370,"journal":{"name":"Proceedings Workshop on Photometric Modeling for Computer Vision and Graphics (Cat. No.PR00271)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132349764","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Simulating DIC microscope images: from physical principles to a computational model","authors":"F. Kagalwala, T. Kanade","doi":"10.1109/PMCVG.1999.787761","DOIUrl":"https://doi.org/10.1109/PMCVG.1999.787761","url":null,"abstract":"Differential Interference Contrast (DIC) microscopy is a powerful visualization tool to study live biological cells. Its use in quantitative analysis, however, is limited by the nonlinear relation between image and object. Combining concepts from graphics and physics, we model these nonlinearities using a generalized ray tracer. We verify our model by comparing real image data of manufactured specimens to simulated images of virtual objects. We plan to use this model to iteratively reconstruct the three-dimensional properties of unknown specimens.","PeriodicalId":309370,"journal":{"name":"Proceedings Workshop on Photometric Modeling for Computer Vision and Graphics (Cat. No.PR00271)","volume":"27 14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115943922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Generation of diffuse and specular appearance from photometric images","authors":"S. Lin","doi":"10.1109/PMCVG.1999.787760","DOIUrl":"https://doi.org/10.1109/PMCVG.1999.787760","url":null,"abstract":"To account for the variability of object appearance due to differences in illumination, attention has recently been focused on representing the set of images for all possible lighting conditions. Approaches that address this problem have primarily focused on lighting differences for diffuse reflection using the Lambertian model; however, specular reflections can additionally present considerable disparity in appearance. We present a method for representing illumination appearance for both diffuse and specular reflections for objects of uniform surface roughness using four photometric images. This approach uses separation of reflection components, extracts surface reflectances and roughness, and produces arbitrary lighting images without explicit computation of surface shape. Experimental results demonstrate the validity of the proposed method for constructing diffuse and specular appearances.","PeriodicalId":309370,"journal":{"name":"Proceedings Workshop on Photometric Modeling for Computer Vision and Graphics (Cat. No.PR00271)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117069790","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Representing spectral functions by a composite model of smooth and spiky components for efficient full-spectrum photorealism","authors":"Yinlong Sun, M. S. Drew, F. Fracchia","doi":"10.1109/PMCVG.1999.787742","DOIUrl":"https://doi.org/10.1109/PMCVG.1999.787742","url":null,"abstract":"We propose a new model called the \"composite model\" to represent spectral functions. This model is built on the idea of decomposing all spectral functions into smooth and spiky components, each with its own distinct representation. A smooth spectrum can be expressed with coefficients of a set of given basis functions, and the discrete spikes in a spiky spectrum with their locations and heights. For the smooth part, we propose re-sampling functions that are reconstructed from the coefficients in a linear combination to improve efficiency. Spectral multiplication is thus greatly reduced in complexity. This new model shows remarkable advantages in representing spectral functions with aspect to accuracy, compactness, computational efficiency, portability, and flexibility, and it has a great application potential in color science, realistic image synthesis, and color image analysis. Here we apply it to rendering images involving real spiky illuminants as well as objects with light dispersion. The composite model is shown to surpass other models in these applications.","PeriodicalId":309370,"journal":{"name":"Proceedings Workshop on Photometric Modeling for Computer Vision and Graphics (Cat. No.PR00271)","volume":"368 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123882984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Surface topography using shape-from-shading","authors":"P. L. Worthington, E. Hancock","doi":"10.1109/PMCVG.1999.787758","DOIUrl":"https://doi.org/10.1109/PMCVG.1999.787758","url":null,"abstract":"This paper demonstrates how a recently reported shape-from-shading scheme can be used to extract topographic information from 2D intensity imagery. The shape-from-shading scheme has two novel ingredients. Firstly, it uses a geometric update procedure which allows the image irradiance equation to be satisfied as a hard-constraint. This not only improves the data-closeness of the recovered needle-map, but also removes the necessity for extensive parameter tuning. Secondly, we use curvature information to impose topographic constraints on the recovered needle-map. The topographic information is captured using the shape-index of Koenderink and VanDoorn (1992) and consistency is imposed using a robust error function. We show that the new shape-from-shading scheme leads to a meaningful topographic labelling of 3D surface structures.","PeriodicalId":309370,"journal":{"name":"Proceedings Workshop on Photometric Modeling for Computer Vision and Graphics (Cat. No.PR00271)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131868147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}