{"title":"Direct recovery of shape from multiple views: a parallax based approach","authors":"Rakesh Kumar, Padmanabhan Anandan, K. Hanna","doi":"10.1109/ICPR.1994.576402","DOIUrl":"https://doi.org/10.1109/ICPR.1994.576402","url":null,"abstract":"Given two arbitrary views of a scene under central projection, if the motion of points on a parametric surface is compensated, the residual parallax displacement field on the reference image is an epipolar field. If the surface aligned is a plane, the parallax magnitude at an image point is directly proportional to the height of the point from the plane and inversely proportional to its depth from the camera. The authors exploit the above theorem to infer 3D height information from oblique aerial 2D images. The authors use direct methods to register the aerial images and develop methods to infer height information under the following three conditions: (i) focal length and image center are both known, (ii) only the focal length is known, and (iii) both are unknown.","PeriodicalId":312019,"journal":{"name":"Proceedings of 12th International Conference on Pattern Recognition","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114209519","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}
H. Netten, I. Young, Michele Prins, L. Vliet, H. Tanke, H. Vrolijk, W. Sloos
{"title":"Automation of fluorescent dot counting in cell nuclei","authors":"H. Netten, I. Young, Michele Prins, L. Vliet, H. Tanke, H. Vrolijk, W. Sloos","doi":"10.1109/ICPR.1994.576231","DOIUrl":"https://doi.org/10.1109/ICPR.1994.576231","url":null,"abstract":"We have developed a completely automated fluorescence microscope system that can examine 500 cells in approximately 20 minutes to determine the number of labeled chromosomes (seen as dots) in each cell nucleus. This system works with two fluorescent dyes-one for the DNA hybridization dots (e.g. FITC) and one for the cell nucleus (e.g. DAPI). After the stage has moved to a new field the image is automatically focused, acquired by a Photometrics KAF 1400 camera, and then analyzed on a Macintosh Quadra 840AV computer. After the required number of cells has been analyzed, the user may interact to correct the computer by working with a gallery of the cell images. The machine accuracies are equal to panels of human experts (manual) and limited by the overlapping of dots in the 3D cell as seen through the 2D projection.","PeriodicalId":312019,"journal":{"name":"Proceedings of 12th International Conference on Pattern Recognition","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116621979","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":"Camera calibration without feature extraction","authors":"L. Robert","doi":"10.1109/ICPR.1994.576411","DOIUrl":"https://doi.org/10.1109/ICPR.1994.576411","url":null,"abstract":"We present an original approach to the problem of camera calibration. Contrary to classical techniques, which first extract the image features and then compute the camera parameters, we directly search for the camera parameters that best map three-dimensional points onto the image edges, characterized as maxims of the intensity gradient or zero-crossings of the Laplacian. Expressed as a one-stage optimization problem over the parameters of the camera, the whole calibration process is solved by classical iterative optimization. We describe experiments on synthetic and real data.","PeriodicalId":312019,"journal":{"name":"Proceedings of 12th International Conference on Pattern Recognition","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125327844","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":"From an intensity image to 3-D segmented descriptions","authors":"M. Zerroug, R. Nevatia","doi":"10.1109/ICPR.1994.576239","DOIUrl":"https://doi.org/10.1109/ICPR.1994.576239","url":null,"abstract":"Addresses the inference of 3-D segmented descriptions of complex objects from a single intensity image. The authors' approach is based on the analysis of the projective properties of a small number of generalized cylinder primitives and their relationships in the image which make up common man-made objects. Past work on this problem has either assumed perfect contours as input or used 2-dimensional shape primitives without relating them to 3-D shape. The method the authors present explicitly uses the 3-dimensionality of the desired descriptions and directly addresses the segmentation problem in the presence of contour breaks, markings shadows and occlusion. This work has many significant applications including recognition of complex curved objects from a single real intensity image. The authors demonstrate their method on real images.","PeriodicalId":312019,"journal":{"name":"Proceedings of 12th International Conference on Pattern Recognition","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122808852","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}
T. Viéville, Emmanuelle Clergue, R. Enciso, H. Mathieu
{"title":"Experimenting 3D vision on a robotic head","authors":"T. Viéville, Emmanuelle Clergue, R. Enciso, H. Mathieu","doi":"10.1109/ICPR.1994.576426","DOIUrl":"https://doi.org/10.1109/ICPR.1994.576426","url":null,"abstract":"We attempt to build a vision system that will allow dynamic 3D-perception of objects of interest. More specifically, we discuss the idea of using 3D visual cues when tracking a visual target, in order to recover some of its 3D characteristics. The experimentation reported corresponds to an implementation of these general ideas by considering a calibrated robotic head. We analyse how to make use of such a system for: (1) detecting 3D-objects of interest, (2) recovering the average depth and size of the tracked objects, and (3) fixating and tracing such objects to facilitate their observation.","PeriodicalId":312019,"journal":{"name":"Proceedings of 12th International Conference on Pattern Recognition","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132566488","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}
Denis Lee, R. Barber, W. Niblack, M. Flickner, J. Hafner, D. Petkovic
{"title":"Indexing for complex queries on a query-by-content image database","authors":"Denis Lee, R. Barber, W. Niblack, M. Flickner, J. Hafner, D. Petkovic","doi":"10.1109/ICPR.1994.576246","DOIUrl":"https://doi.org/10.1109/ICPR.1994.576246","url":null,"abstract":"We describe how the QBIC (Query By Image Content) system handles \"multi-*\" queries-queries on large image collections involving multifeatures of each image as a whole and of multiple objects within each image. The queries are based on properties of image content-such as colors, textures, shapes, and edges. The system computes a set of features to describe the above properties, uses distance-like measures on the features to provide similarity based retrieval, and has a graphical interface that enable users pose queries visually. In this paper, we present QBIC indexing algorithms that allow these \"multi-*\" queries to run efficiently.","PeriodicalId":312019,"journal":{"name":"Proceedings of 12th International Conference on Pattern Recognition","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133738482","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":"Improved 3-D shape recovery and correction algorithm from a single view","authors":"Jufu Feng, Qingyun Shi","doi":"10.1109/ICPR.1994.576406","DOIUrl":"https://doi.org/10.1109/ICPR.1994.576406","url":null,"abstract":"In this paper, we develop an improved algorithm to recover and correct polyhedron from a given line drawing. It can immediately recover the polyhedron even if image data are incorrect due to vertex-position errors. Many experiments have been done to demonstrate the algorithm to be effective and efficient and show that the speed of recovery and correction is greatly improved and one of experiments is given.","PeriodicalId":312019,"journal":{"name":"Proceedings of 12th International Conference on Pattern Recognition","volume":"201 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133387847","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":"Virtual line segment-based Hough transform","authors":"Ji Y. Chang, A. Hanson","doi":"10.1109/ICPR.1994.576226","DOIUrl":"https://doi.org/10.1109/ICPR.1994.576226","url":null,"abstract":"The generalized Hough transform (GHough) is a useful technique for detecting and locating 2D shapes. However, GHough requires a 4D accumulator array to detect objects of unknown scale and orientation. In this paper, we propose an extension of GHough, the virtual line segment-based Hough transform (VHough) that requires much less storage than GHough to accurately determine the scale and orientation of an object instance. VHough takes O(N/sup 2/) time, where N is the number of edge pixels in an image, but requires only 2D accumulator array for the detection of arbitrarily rotated and scaled objects. We present an experimental result to show that VHough is well-suited to recognition tasks when no a priori knowledge about parameters is available.","PeriodicalId":312019,"journal":{"name":"Proceedings of 12th International Conference on Pattern Recognition","volume":"22 5-6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114048278","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":"Multi-temperature annealing: a new approach for the energy-minimization of hierarchical Markov random field models","authors":"J. Zerubia, Z. Kato, M. Berthod","doi":"10.1109/ICPR.1994.576342","DOIUrl":"https://doi.org/10.1109/ICPR.1994.576342","url":null,"abstract":"As it is well known, optimization of the energy function of Markov random fields is very expensive. Hierarchical models have usually much more communication per pixel than monogrid ones. This is why classical annealing schemes are too slow, even on a parallel machine, to minimize the energy associated with such a model. However, taking benefit of the pyramidal structure of the model, we can define a new annealing scheme: the multitemperature annealing (MTA), which consists of associating higher temperatures to coarser levels, in order to be less sensitive to local minima at coarser grids. The convergence to the global optimum is proved by a generalisation of the annealing theorem of Geman and Geman (1984). We have applied the algorithm to image classification and tested it on synthetic and real images.","PeriodicalId":312019,"journal":{"name":"Proceedings of 12th International Conference on Pattern Recognition","volume":"226 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115834940","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":"How to track efficiently piecewise curved contours with a view to reconstructing 3D objects","authors":"M. Berger","doi":"10.1109/ICPR.1994.576221","DOIUrl":"https://doi.org/10.1109/ICPR.1994.576221","url":null,"abstract":"This paper addresses the problem of rigid and nonpolyhedral object tracking in complex environments without a priori knowledge neither on objects nor on the camera motion. The key of our approach is to propose a robust curve based tracking algorithm founded on an iterative registration method and exploiting our rigid snake model. In order to ensure the convergence of the tracking process, we then present supervision strategies we have developed to control both the prediction step and the snake convergence. Finally, since recovering accurate contour localization is important for reconstruction task, we propose a cooperative use of the snake model and of a corner detector to finely detect piecewise curved contours.","PeriodicalId":312019,"journal":{"name":"Proceedings of 12th International Conference on Pattern Recognition","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125423678","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}