Pub Date : 2004-03-28DOI: 10.1109/IAI.2004.1300942
Michael G. Grant, Jamie D. Shutler, M. Nixon, J. Carter
There is an increasing need in biometric deployment, especially gait, for extraction in unconstrained scenes. Extraction in such circumstances is problematic and requires noise-resistant algorithms. We describe novel methods that enable generic extraction of moving objects, but particularly walking people, from large outdoor video databases. Combining the techniques into a preprocessing chain, we apply them to the NIST Gait Challenge database. This produces visually good extracted data suitable for biometric use. Analysis of the output by multiple gait biometrics yields encouraging recognition results, which approach those obtained from laboratory quality data.
{"title":"Analysis of a human extraction system for deploying gait biometrics","authors":"Michael G. Grant, Jamie D. Shutler, M. Nixon, J. Carter","doi":"10.1109/IAI.2004.1300942","DOIUrl":"https://doi.org/10.1109/IAI.2004.1300942","url":null,"abstract":"There is an increasing need in biometric deployment, especially gait, for extraction in unconstrained scenes. Extraction in such circumstances is problematic and requires noise-resistant algorithms. We describe novel methods that enable generic extraction of moving objects, but particularly walking people, from large outdoor video databases. Combining the techniques into a preprocessing chain, we apply them to the NIST Gait Challenge database. This produces visually good extracted data suitable for biometric use. Analysis of the output by multiple gait biometrics yields encouraging recognition results, which approach those obtained from laboratory quality data.","PeriodicalId":326040,"journal":{"name":"6th IEEE Southwest Symposium on Image Analysis and Interpretation, 2004.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124850250","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 : 2004-03-28DOI: 10.1109/IAI.2004.1300965
Jinshan Tang, S. Acton
The paper proposes a new gradient vector flow (GVF) snake based on the discrete cosine transform (DCT) for object boundary detection. In order to develop the DCT GVF snake, for each pixel in the spatial domain, we compute the two dimensional DCT in its local neighborhood. A contrast measure derived from the local DCT coefficients is used to compute the gradient vector flow field, which is employed as the external force to drive the snake to the object edges. The advantage of the DCT GVF snake lies in its robustness to multiplicative noise. The DCT GVF snake is applied to object boundary detection in images with multiplicative noise. Experiments show the boundary detection result obtained by the DCT GVF snake is more accurate than that obtained by the original GVF snake.
{"title":"A DCT based gradient vector flow snake for object boundary detection","authors":"Jinshan Tang, S. Acton","doi":"10.1109/IAI.2004.1300965","DOIUrl":"https://doi.org/10.1109/IAI.2004.1300965","url":null,"abstract":"The paper proposes a new gradient vector flow (GVF) snake based on the discrete cosine transform (DCT) for object boundary detection. In order to develop the DCT GVF snake, for each pixel in the spatial domain, we compute the two dimensional DCT in its local neighborhood. A contrast measure derived from the local DCT coefficients is used to compute the gradient vector flow field, which is employed as the external force to drive the snake to the object edges. The advantage of the DCT GVF snake lies in its robustness to multiplicative noise. The DCT GVF snake is applied to object boundary detection in images with multiplicative noise. Experiments show the boundary detection result obtained by the DCT GVF snake is more accurate than that obtained by the original GVF snake.","PeriodicalId":326040,"journal":{"name":"6th IEEE Southwest Symposium on Image Analysis and Interpretation, 2004.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125841801","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 : 2004-03-28DOI: 10.1109/IAI.2004.1300975
S. Shiitani, T. Baba, S. Endo, Y. Uehara, D. Masumoto, S. Nagata
We propose a technique for efficient retrieval of video scenes in a large number of digital videos. With the technique, cut frame images are automatically detected from videos, and arranged based on a visual feature in a virtual 3D space so that users can easily catch out the target image. We conducted experiments to confirm the effectiveness of the technique. The results show that retrieval by our technique is about 20 times as fast as retrieval by the fast forward playing mode at three times the normal speed.
{"title":"Efficient video retrieval system using virtual 3D space","authors":"S. Shiitani, T. Baba, S. Endo, Y. Uehara, D. Masumoto, S. Nagata","doi":"10.1109/IAI.2004.1300975","DOIUrl":"https://doi.org/10.1109/IAI.2004.1300975","url":null,"abstract":"We propose a technique for efficient retrieval of video scenes in a large number of digital videos. With the technique, cut frame images are automatically detected from videos, and arranged based on a visual feature in a virtual 3D space so that users can easily catch out the target image. We conducted experiments to confirm the effectiveness of the technique. The results show that retrieval by our technique is about 20 times as fast as retrieval by the fast forward playing mode at three times the normal speed.","PeriodicalId":326040,"journal":{"name":"6th IEEE Southwest Symposium on Image Analysis and Interpretation, 2004.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126082489","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 : 2004-03-28DOI: 10.1109/IAI.2004.1300940
S. Harasse, L. Bonnaud, A. Caplier, M. Desvignes
Surveillance systems depend greatly on the robustness and availability of the video streams. The cameras must deliver reliable streams from an angle corresponding to the correct viewpoint. In other words, the field of view and video quality must remain unchanged after the initial installation of a surveillance camera. The paper proposes an approach to detect changes (such as displacement, out of focus, obstruction) automatically in a difficult environment with illumination variations and dynamic background and foreground objects.
{"title":"Automated camera dysfunctions detection","authors":"S. Harasse, L. Bonnaud, A. Caplier, M. Desvignes","doi":"10.1109/IAI.2004.1300940","DOIUrl":"https://doi.org/10.1109/IAI.2004.1300940","url":null,"abstract":"Surveillance systems depend greatly on the robustness and availability of the video streams. The cameras must deliver reliable streams from an angle corresponding to the correct viewpoint. In other words, the field of view and video quality must remain unchanged after the initial installation of a surveillance camera. The paper proposes an approach to detect changes (such as displacement, out of focus, obstruction) automatically in a difficult environment with illumination variations and dynamic background and foreground objects.","PeriodicalId":326040,"journal":{"name":"6th IEEE Southwest Symposium on Image Analysis and Interpretation, 2004.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131659438","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 : 2004-03-28DOI: 10.1109/IAI.2004.1300941
M. Magnor, C. Theobalt
We describe a method to analyze multiple synchronized video streams by making use of a parameterized geometry model of the recorded object. By formulating the task of fitting the model to the images in terms of optimizing silhouette match, we are able to capture the time-varying 3D pose of the object automatically and robustly. To evaluate the energy functional, we exploit the fast image synthesis capabilities of a conventional PC graphics card. The use of an a-priori object model enables us to enforce kinematic constraints as well as temporal coherence, and we obtain a high-quality surface description as output. Suitably modified, the presented technique is also applicable to medical and other image analysis tasks if a parameterized, generic geometry model of the object of interest is available.
{"title":"Model-based analysis of multi-video data","authors":"M. Magnor, C. Theobalt","doi":"10.1109/IAI.2004.1300941","DOIUrl":"https://doi.org/10.1109/IAI.2004.1300941","url":null,"abstract":"We describe a method to analyze multiple synchronized video streams by making use of a parameterized geometry model of the recorded object. By formulating the task of fitting the model to the images in terms of optimizing silhouette match, we are able to capture the time-varying 3D pose of the object automatically and robustly. To evaluate the energy functional, we exploit the fast image synthesis capabilities of a conventional PC graphics card. The use of an a-priori object model enables us to enforce kinematic constraints as well as temporal coherence, and we obtain a high-quality surface description as output. Suitably modified, the presented technique is also applicable to medical and other image analysis tasks if a parameterized, generic geometry model of the object of interest is available.","PeriodicalId":326040,"journal":{"name":"6th IEEE Southwest Symposium on Image Analysis and Interpretation, 2004.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133953574","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 : 2004-03-28DOI: 10.1109/IAI.2004.1300964
G. Martín, M. Pattichis
The study of the effects of scanning on texture features is of great interest to computer-based screening systems. A mathematical model is developed for understanding how the original image gets distorted due to the contrast variability and geometric distortion inherent in the scanning process. Both quantitative and qualitative results (for sixty common texture features) are given.
{"title":"The characterization of scanning noise and quantization on texture feature analysis","authors":"G. Martín, M. Pattichis","doi":"10.1109/IAI.2004.1300964","DOIUrl":"https://doi.org/10.1109/IAI.2004.1300964","url":null,"abstract":"The study of the effects of scanning on texture features is of great interest to computer-based screening systems. A mathematical model is developed for understanding how the original image gets distorted due to the contrast variability and geometric distortion inherent in the scanning process. Both quantitative and qualitative results (for sixty common texture features) are given.","PeriodicalId":326040,"journal":{"name":"6th IEEE Southwest Symposium on Image Analysis and Interpretation, 2004.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126200144","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 : 2004-03-28DOI: 10.1109/IAI.2004.1300950
R. Brockers, M. Hund, B. Mertsching
We introduce a novel stereo algorithm for computing a disparity map from a stereo image pair by minimizing a global cost function. The approach consists of two steps. First a "traditional" correlation-based similarity measurement is performed, then a relaxation takes place to eliminate possible ambiguities. The relaxation is formulated as a cost-optimizing approach, taking into account both the stereoscopic continuity constraint and considerations of the pixel similarity. The special formulation guarantees the existence of a unique minimum of the cost function which can be easily and rapidly found by standard numerical procedures. Results on real and synthetic images demonstrate the operative potential of the approach.
{"title":"Fast stereo vision for mobile robots by global minima of cost functions","authors":"R. Brockers, M. Hund, B. Mertsching","doi":"10.1109/IAI.2004.1300950","DOIUrl":"https://doi.org/10.1109/IAI.2004.1300950","url":null,"abstract":"We introduce a novel stereo algorithm for computing a disparity map from a stereo image pair by minimizing a global cost function. The approach consists of two steps. First a \"traditional\" correlation-based similarity measurement is performed, then a relaxation takes place to eliminate possible ambiguities. The relaxation is formulated as a cost-optimizing approach, taking into account both the stereoscopic continuity constraint and considerations of the pixel similarity. The special formulation guarantees the existence of a unique minimum of the cost function which can be easily and rapidly found by standard numerical procedures. Results on real and synthetic images demonstrate the operative potential of the approach.","PeriodicalId":326040,"journal":{"name":"6th IEEE Southwest Symposium on Image Analysis and Interpretation, 2004.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129633002","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 : 2004-03-28DOI: 10.1109/IAI.2004.1300973
R.V. Paul, M. Pattichis
AM-FM models images as a linear combination of positive amplitude modulated (AM) sinusoids with non-linear phase functions. We develop a novel FM harmonics operator for revealing different levels of image structure detail. The new operator is defined in terms of known AM-FM demodulation techniques: dominant component analysis and channelized component analysis. We also show an example of image segmentation, where the new operator is used for tracking cardiac wall boundaries in motion-mode (M-mode) ultrasound video.
{"title":"Nested random phase sequence sets: a link between AM-FM demodulation and increasing operators with application to cardiac image analysis","authors":"R.V. Paul, M. Pattichis","doi":"10.1109/IAI.2004.1300973","DOIUrl":"https://doi.org/10.1109/IAI.2004.1300973","url":null,"abstract":"AM-FM models images as a linear combination of positive amplitude modulated (AM) sinusoids with non-linear phase functions. We develop a novel FM harmonics operator for revealing different levels of image structure detail. The new operator is defined in terms of known AM-FM demodulation techniques: dominant component analysis and channelized component analysis. We also show an example of image segmentation, where the new operator is used for tracking cardiac wall boundaries in motion-mode (M-mode) ultrasound video.","PeriodicalId":326040,"journal":{"name":"6th IEEE Southwest Symposium on Image Analysis and Interpretation, 2004.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122156112","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 : 2004-03-28DOI: 10.1109/IAI.2004.1300957
M. Trujillo, M. Sadki
Correspondence analysis (CA) is a powerful data analysis and decision support statistical method which provides information about the relative contribution of the different factors extracted from datasets under analysis. This method is used for dimensionality reduction and clustering interpretation in a wide range of applications. Our contribution highlights one of CA's potential application in the field of texture features extraction and classification in addition to demonstrating its capability of optimizing a nonlinear transformation of the grey level which may cause problems in other methods. A novel decision support image representation is introduced; its functionality is described and it is validated using nondestructive industrial inspection (NDII) and remote sensing satellite imagery. The behaviour of the new system is studied and its optimal parameters for texture recognition and dimensionality reduction are established by using factors analysis.
{"title":"Correspondence analysis applied to textural features recognition","authors":"M. Trujillo, M. Sadki","doi":"10.1109/IAI.2004.1300957","DOIUrl":"https://doi.org/10.1109/IAI.2004.1300957","url":null,"abstract":"Correspondence analysis (CA) is a powerful data analysis and decision support statistical method which provides information about the relative contribution of the different factors extracted from datasets under analysis. This method is used for dimensionality reduction and clustering interpretation in a wide range of applications. Our contribution highlights one of CA's potential application in the field of texture features extraction and classification in addition to demonstrating its capability of optimizing a nonlinear transformation of the grey level which may cause problems in other methods. A novel decision support image representation is introduced; its functionality is described and it is validated using nondestructive industrial inspection (NDII) and remote sensing satellite imagery. The behaviour of the new system is studied and its optimal parameters for texture recognition and dimensionality reduction are established by using factors analysis.","PeriodicalId":326040,"journal":{"name":"6th IEEE Southwest Symposium on Image Analysis and Interpretation, 2004.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124140852","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 : 2004-03-28DOI: 10.1109/IAI.2004.1300936
J. Fortuna, P. Quick, D. Capson
A comparison of the accuracy of visual position measurement in four common subspaces is presented. Principal component analysis (PCA), independent component analysis (ICA), kernel principal component analysis (KPCA) and Fisher's linear discriminant (FLD) are examined for their ability to discriminate positions in a 2D visual subspace. The comparison was done with both constant and varying illumination and random occlusion. It is shown that PCA provides very good overall performance compared with more sophisticated techniques such as ICA, FLD, and KPCA, at a reduced computational complexity.
{"title":"A comparison of subspace methods for accurate position measurement","authors":"J. Fortuna, P. Quick, D. Capson","doi":"10.1109/IAI.2004.1300936","DOIUrl":"https://doi.org/10.1109/IAI.2004.1300936","url":null,"abstract":"A comparison of the accuracy of visual position measurement in four common subspaces is presented. Principal component analysis (PCA), independent component analysis (ICA), kernel principal component analysis (KPCA) and Fisher's linear discriminant (FLD) are examined for their ability to discriminate positions in a 2D visual subspace. The comparison was done with both constant and varying illumination and random occlusion. It is shown that PCA provides very good overall performance compared with more sophisticated techniques such as ICA, FLD, and KPCA, at a reduced computational complexity.","PeriodicalId":326040,"journal":{"name":"6th IEEE Southwest Symposium on Image Analysis and Interpretation, 2004.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2004-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116452345","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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