Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234018
E. Holden, R. Owens
The paper presents a new hand shape representation technique that characterises the finger-only topology of the hand, by adapting an existing technique from speech signal processing. From a moving hand sequence, the tracking algorithm determines the centre of the largest convex subset of the hand, using a combination of pattern matching and condensation algorithms. A hand shape feature represents the topological formation of the finger-only regions of the hand using a linear predictive coding parameter set called cepstral coefficients. Experimental results demonstrate the effectiveness of detecting the shape feature from motion sequences.
{"title":"Recognising moving hand shapes","authors":"E. Holden, R. Owens","doi":"10.1109/ICIAP.2003.1234018","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234018","url":null,"abstract":"The paper presents a new hand shape representation technique that characterises the finger-only topology of the hand, by adapting an existing technique from speech signal processing. From a moving hand sequence, the tracking algorithm determines the centre of the largest convex subset of the hand, using a combination of pattern matching and condensation algorithms. A hand shape feature represents the topological formation of the finger-only regions of the hand using a linear predictive coding parameter set called cepstral coefficients. Experimental results demonstrate the effectiveness of detecting the shape feature from motion sequences.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121921088","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}
Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234050
L. Cinque, S. Levialdi, A. Malizia
Paper document recognition is fundamental for office automation becoming every day a more powerful tool in those fields where information is still on paper. Document recognition follows from data acquisition, from both journals and entire books, in order to transform them into digital objects. We present a new system for document recognition that follows the open source methodologies, XML description for document segmentation and classification, which turns out to be beneficial in terms of classification precision, and general-purpose availability.
{"title":"A system for the automatic layout segmentation and classification of digital documents","authors":"L. Cinque, S. Levialdi, A. Malizia","doi":"10.1109/ICIAP.2003.1234050","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234050","url":null,"abstract":"Paper document recognition is fundamental for office automation becoming every day a more powerful tool in those fields where information is still on paper. Document recognition follows from data acquisition, from both journals and entire books, in order to transform them into digital objects. We present a new system for document recognition that follows the open source methodologies, XML description for document segmentation and classification, which turns out to be beneficial in terms of classification precision, and general-purpose availability.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"67 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131020725","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}
Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234095
A. Robles-Kelly, E. Hancock
We explore how spectral methods for graph seriation can be used to develop a new shape-from-shading algorithm. We characterise the field of surface normals using a transition matrix whose elements are computed from the sectional curvature between different image locations. We use a graph seriation method to define a curvature minimising surface integration path for the purposes of height reconstruction. To smooth the reconstructed surface, we fit quadric patches to the height data. The smoothed surface normal directions are updated ensuring compliance with Lambert's law. The processes of height recovery and surface normal adjustment are interleaved and iterated until a stable surface is obtained. We provide results on synthetic and real-world imagery.
{"title":"An eigenvector method for shape-from-shading","authors":"A. Robles-Kelly, E. Hancock","doi":"10.1109/ICIAP.2003.1234095","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234095","url":null,"abstract":"We explore how spectral methods for graph seriation can be used to develop a new shape-from-shading algorithm. We characterise the field of surface normals using a transition matrix whose elements are computed from the sectional curvature between different image locations. We use a graph seriation method to define a curvature minimising surface integration path for the purposes of height reconstruction. To smooth the reconstructed surface, we fit quadric patches to the height data. The smoothed surface normal directions are updated ensuring compliance with Lambert's law. The processes of height recovery and surface normal adjustment are interleaved and iterated until a stable surface is obtained. We provide results on synthetic and real-world imagery.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125957815","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}
Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234077
P. Baldassarri, P. Puliti, A. Montesanto, G. Tascini
The paper proposes a machine learning method for self-localising a mobile agent, using the images supplied by a single omni-directional camera. The images acquired by the camera may be viewed as an implicit topological representation of the environment. The environment is a priori unknown and the topological representation is derived by unsupervised neural network architecture. The architecture includes a self-organising neural network, and is constituted by a growing neural gas, which is well known for its topology preserving quality. The growth depends on the topology that is not a priori defined, and on the need of discovering it, by the neural network, during the learning. The implemented system is able to recognise correctly the input frames and to reconstruct a topological map of the environment. Each node of the neural network identifies a single zone of the environment and the connections between the nodes correspond to the real space connections in the environment.
{"title":"Visual self-localisation using automatic topology construction","authors":"P. Baldassarri, P. Puliti, A. Montesanto, G. Tascini","doi":"10.1109/ICIAP.2003.1234077","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234077","url":null,"abstract":"The paper proposes a machine learning method for self-localising a mobile agent, using the images supplied by a single omni-directional camera. The images acquired by the camera may be viewed as an implicit topological representation of the environment. The environment is a priori unknown and the topological representation is derived by unsupervised neural network architecture. The architecture includes a self-organising neural network, and is constituted by a growing neural gas, which is well known for its topology preserving quality. The growth depends on the topology that is not a priori defined, and on the need of discovering it, by the neural network, during the learning. The implemented system is able to recognise correctly the input frames and to reconstruct a topological map of the environment. Each node of the neural network identifies a single zone of the environment and the connections between the nodes correspond to the real space connections in the environment.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126571740","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}
Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234048
R. Strzodka, Ivo Ihrke, M. Magnor
The generalized Hough transform constitutes a wellknown approach to object recognition and pose detection. To attain reliable detection results, however, a very large number of candidate object poses and scale factors need to be considered. We employ an inexpensive, consumer-market graphics-card as the "poor man's" parallel processing system. We describe the implementation of a fast and enhanced version of the generalized Hough transform on graphics hardware. Thanks to the high bandwidth of on-board texture memory, a single pose can be evaluated in less than 3 ms, independent of the number of edge pixels in the image. From known object geometry, our hardware-accelerated generalized Hough transform algorithm is capable of detecting an object's 3D pose, scale, and position in the image within less than one minute. A good pose estimation is even delivered in less than 10 seconds.
{"title":"A graphics hardware implementation of the generalized Hough transform for fast object recognition, scale, and 3D pose detection","authors":"R. Strzodka, Ivo Ihrke, M. Magnor","doi":"10.1109/ICIAP.2003.1234048","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234048","url":null,"abstract":"The generalized Hough transform constitutes a wellknown approach to object recognition and pose detection. To attain reliable detection results, however, a very large number of candidate object poses and scale factors need to be considered. We employ an inexpensive, consumer-market graphics-card as the \"poor man's\" parallel processing system. We describe the implementation of a fast and enhanced version of the generalized Hough transform on graphics hardware. Thanks to the high bandwidth of on-board texture memory, a single pose can be evaluated in less than 3 ms, independent of the number of edge pixels in the image. From known object geometry, our hardware-accelerated generalized Hough transform algorithm is capable of detecting an object's 3D pose, scale, and position in the image within less than one minute. A good pose estimation is even delivered in less than 10 seconds.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114508920","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}
Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234044
J. Kautz, H. Lensch, M. Goesele, J. Lang, H. Seidel
High quality, virtual 3D models are quickly emerging as a new multimedia data type with applications in such diverse areas as e-commerce, online encyclopaedias, or virtual museums, to name just a few. The paper presents new algorithms and techniques for the acquisition and real-time interaction with complex textured 3D objects and shows how these results can be seamlessly integrated with previous work into a single framework for the acquisition, processing, and interactive display of high quality 3D models. In addition to pure geometry, such algorithms also have to take into account the texture of an object (which is crucial for a realistic appearance) and its reflectance behavior. The measurement of accurate material properties is an important step towards photorealistic rendering, where both the general surface properties as well as the spatially varying effects of the object are needed. Recent work on the image-based reconstruction of spatially varying BRDFs (bidirectional reflectance distribution function) enables the generation of high quality models of real objects from a sparse set of input data. Efficient use of the capabilities of advanced PC graphics hardware allows for interactive rendering under arbitrary viewing and lighting conditions and realistically reproduces the appearance of the original object.
{"title":"Modeling the world: the virtualization pipeline","authors":"J. Kautz, H. Lensch, M. Goesele, J. Lang, H. Seidel","doi":"10.1109/ICIAP.2003.1234044","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234044","url":null,"abstract":"High quality, virtual 3D models are quickly emerging as a new multimedia data type with applications in such diverse areas as e-commerce, online encyclopaedias, or virtual museums, to name just a few. The paper presents new algorithms and techniques for the acquisition and real-time interaction with complex textured 3D objects and shows how these results can be seamlessly integrated with previous work into a single framework for the acquisition, processing, and interactive display of high quality 3D models. In addition to pure geometry, such algorithms also have to take into account the texture of an object (which is crucial for a realistic appearance) and its reflectance behavior. The measurement of accurate material properties is an important step towards photorealistic rendering, where both the general surface properties as well as the spatially varying effects of the object are needed. Recent work on the image-based reconstruction of spatially varying BRDFs (bidirectional reflectance distribution function) enables the generation of high quality models of real objects from a sparse set of input data. Efficient use of the capabilities of advanced PC graphics hardware allows for interactive rendering under arbitrary viewing and lighting conditions and realistically reproduces the appearance of the original object.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114257810","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}
Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234060
S. Barotti, L. Lombardi, P. Lombardi
In this paper, we address two of the common faults of indoor background modeling, namely the light switch and the bootstrapping problems. Light switch concerns sudden changes in lighting conditions that cause the failure of a background model of the scene. Bootstrapping problems occur when a training sequence free of moving objects is not available for model building. Our study investigates how rearrangements in the structure of multi-modular vision systems can improve the system performance in a changing environment. In other words, we want to introduce in the system the capability to select the most reliable method for extracting useful information among those available, and to exclude inadequate modules from the flow of signal analysis.
{"title":"Multi-module switching and fusion for robust video surveillance","authors":"S. Barotti, L. Lombardi, P. Lombardi","doi":"10.1109/ICIAP.2003.1234060","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234060","url":null,"abstract":"In this paper, we address two of the common faults of indoor background modeling, namely the light switch and the bootstrapping problems. Light switch concerns sudden changes in lighting conditions that cause the failure of a background model of the scene. Bootstrapping problems occur when a training sequence free of moving objects is not available for model building. Our study investigates how rearrangements in the structure of multi-modular vision systems can improve the system performance in a changing environment. In other words, we want to introduce in the system the capability to select the most reliable method for extracting useful information among those available, and to exclude inadequate modules from the flow of signal analysis.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127811232","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}
Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234117
P. Leclercq, John Morris
We have measured the performance of several area-based stereo matching algorithms with noise added to synthetic images. Dense disparity maps were computed and compared with the ground truth using three metrics: the fraction of correctly computed disparities, the mean and the standard deviation of the disparity error distribution. For a noise-free image, S. Birchfield and C. Tomasi's pixel-to-pixel dynamic algorithm performed slightly better than a simple sum-of-absolute-differences algorithm (67% correct matches vs 65%) $considered to be within experimental error. A census algorithm performed worst at only 54%. The dynamic algorithm performed well until the S/N ratio reached 36 dB after which its performance started to drop. However, with correctly chosen parameters, it was superior to correlation and census algorithms until the images became very noisy (/spl sim/15 dB). The dynamic algorithm also ran faster than the fastest correlation algorithms using an optimum window radius of 4, and more than 10 times faster than the census algorithm.
{"title":"Robustness to noise of stereo matching","authors":"P. Leclercq, John Morris","doi":"10.1109/ICIAP.2003.1234117","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234117","url":null,"abstract":"We have measured the performance of several area-based stereo matching algorithms with noise added to synthetic images. Dense disparity maps were computed and compared with the ground truth using three metrics: the fraction of correctly computed disparities, the mean and the standard deviation of the disparity error distribution. For a noise-free image, S. Birchfield and C. Tomasi's pixel-to-pixel dynamic algorithm performed slightly better than a simple sum-of-absolute-differences algorithm (67% correct matches vs 65%) $considered to be within experimental error. A census algorithm performed worst at only 54%. The dynamic algorithm performed well until the S/N ratio reached 36 dB after which its performance started to drop. However, with correctly chosen parameters, it was superior to correlation and census algorithms until the images became very noisy (/spl sim/15 dB). The dynamic algorithm also ran faster than the fastest correlation algorithms using an optimum window radius of 4, and more than 10 times faster than the census algorithm.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127980052","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}
Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234023
V. Gesù, Giosuè Lo Bosco, B. Zavidovique
The paper shows an application of a new operator named the iterated object transform (IOT) for cell classification. The IOT has the ability to grasp the internal structure of a digital object and this feature can be usefully applied to discriminate structured images. This is the case of cells representing chondrocytes in bone tissue, giarda protozoan, and myeloid leukaemia. A tree classifier allows us to discriminate the three classes with a good accuracy.
{"title":"Classification based on iterative object symmetry transform","authors":"V. Gesù, Giosuè Lo Bosco, B. Zavidovique","doi":"10.1109/ICIAP.2003.1234023","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234023","url":null,"abstract":"The paper shows an application of a new operator named the iterated object transform (IOT) for cell classification. The IOT has the ability to grasp the internal structure of a digital object and this feature can be usefully applied to discriminate structured images. This is the case of cells representing chondrocytes in bone tissue, giarda protozoan, and myeloid leukaemia. A tree classifier allows us to discriminate the three classes with a good accuracy.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116963882","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}
Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234114
S. Cuenca
The paper presents a new efficient approach to texture analysis based on distributions of simple spatial and tonal relationships. The texture description proposed makes use of a semicover concept over binary planes derived from grey images. A measure of the local semicover tendency based on joint occurrences of elementary semicover patterns is described, and a computation simplification method is presented to reduce the computational cost. The method presents a reduced set of parameters that facilitates its optimization in different types of application. The performance of the method is evaluated by means of a comparative study, including other algorithms widely used in texture analysis. The results show a similar or superior performance to other more complex approaches.
{"title":"Texture analysis based on local semicovers","authors":"S. Cuenca","doi":"10.1109/ICIAP.2003.1234114","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234114","url":null,"abstract":"The paper presents a new efficient approach to texture analysis based on distributions of simple spatial and tonal relationships. The texture description proposed makes use of a semicover concept over binary planes derived from grey images. A measure of the local semicover tendency based on joint occurrences of elementary semicover patterns is described, and a computation simplification method is presented to reduce the computational cost. The method presents a reduced set of parameters that facilitates its optimization in different types of application. The performance of the method is evaluated by means of a comparative study, including other algorithms widely used in texture analysis. The results show a similar or superior performance to other more complex approaches.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2003-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115476849","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}
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