Pub Date : 2003-09-17DOI: 10.1109/ICIAP.2003.1234026
C. Conde, Antonio Ruiz, E. Cabello
Principal components analysis (PCA) has been one of the most applied methods for face verification using only 2D information, in fact, PCA is practically the method of choice for face verification applications in the real-world. An alternative method to reduce the problem dimension is working with low resolution images. In our experiments, three classifiers have been considered to compare the results achieved using PCA versus the results obtained using low resolution images. An initial set of located faces has been used for PCA matrix computation and for training all classifiers. The images belonging to the testing set were chosen to be different from the training ones. Classifiers considered are k-nearest neighbours (KNN), radial basis function (RBF) artificial neural networks, and support vector machine (SVM). Results show that SVM always achieves better results than the other classifiers. With SVM, correct verification difference between PCA and low resolution processing is only 0.13% (99.52% against 99.39%).
{"title":"PCA vs low resolution images in face verification","authors":"C. Conde, Antonio Ruiz, E. Cabello","doi":"10.1109/ICIAP.2003.1234026","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234026","url":null,"abstract":"Principal components analysis (PCA) has been one of the most applied methods for face verification using only 2D information, in fact, PCA is practically the method of choice for face verification applications in the real-world. An alternative method to reduce the problem dimension is working with low resolution images. In our experiments, three classifiers have been considered to compare the results achieved using PCA versus the results obtained using low resolution images. An initial set of located faces has been used for PCA matrix computation and for training all classifiers. The images belonging to the testing set were chosen to be different from the training ones. Classifiers considered are k-nearest neighbours (KNN), radial basis function (RBF) artificial neural networks, and support vector machine (SVM). Results show that SVM always achieves better results than the other classifiers. With SVM, correct verification difference between PCA and low resolution processing is only 0.13% (99.52% against 99.39%).","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"53 3 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":"133635032","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.2003.1234031
M. Hild, Motonobu Hashimoto, Kazunobu Yoshida
We propose an object recognition method in which the identity of objects is determined by observing the finger pointing action of persons. The system determines the head and hands regions, tracks them in real time, and verifies them through an analysis of 3D data points. Then it determines the pointing direction and intersects it with an environment model. Intersection computations are based on potential field models for both the finger pointing process and the object representations.
{"title":"Object recognition via recognition of finger pointing actions","authors":"M. Hild, Motonobu Hashimoto, Kazunobu Yoshida","doi":"10.1109/ICIAP.2003.1234031","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234031","url":null,"abstract":"We propose an object recognition method in which the identity of objects is determined by observing the finger pointing action of persons. The system determines the head and hands regions, tracks them in real time, and verifies them through an analysis of 3D data points. Then it determines the pointing direction and intersects it with an environment model. Intersection computations are based on potential field models for both the finger pointing process and the object representations.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"39 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":"132471402","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.2003.1234034
L. Panini, R. Cucchiara
This paper describes an approach for human posture classification that has been devised for indoor surveillance in domotic applications. The approach was initially inspired to a previous work of Haritaoglou et al. (1998) that uses histogram projections to classify people's posture. We modify and improve the generality of the approach by adding a machine learning phase in order to generate probability maps. A statistic classifier has then defined that compares the probability maps and the histogram profiles extracted from each of the moving people. The approach is very robust if the initial constraints are satisfied and exhibits a very low computational time so that it can be used to process live videos with standard platforms.
{"title":"A machine learning approach for human posture detection in domotics applications","authors":"L. Panini, R. Cucchiara","doi":"10.1109/ICIAP.2003.1234034","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234034","url":null,"abstract":"This paper describes an approach for human posture classification that has been devised for indoor surveillance in domotic applications. The approach was initially inspired to a previous work of Haritaoglou et al. (1998) that uses histogram projections to classify people's posture. We modify and improve the generality of the approach by adding a machine learning phase in order to generate probability maps. A statistic classifier has then defined that compares the probability maps and the histogram profiles extracted from each of the moving people. The approach is very robust if the initial constraints are satisfied and exhibits a very low computational time so that it can be used to process live videos with standard platforms.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"38 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":"131687497","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.2003.1234081
I. Gerace, R. Pandolfi
We focus our attention on the problem of restoring a color image corrupted by blur and noise. This problem is ill-posed in the Hadamard sense. By regularization techniques, it is possible to define the solution of the problem as the minimum of an energy function. To improve the quality of the reconstruction, some Boolean variables, associated with the discontinuities of the intensity color field, are introduced. Such variables, called line variables, have to be estimated and can be used in the energy function in an implicit way. Moreover, we impose that adjacent discontinuities have not to be parallel. To minimize the energy function, a CATILED (convex approximation technique for interacting line elements deblurring) algorithm is used. The experimental results confirm the good qualities of this technique.
{"title":"A color image restoration with adjacent parallel lines inhibition","authors":"I. Gerace, R. Pandolfi","doi":"10.1109/ICIAP.2003.1234081","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234081","url":null,"abstract":"We focus our attention on the problem of restoring a color image corrupted by blur and noise. This problem is ill-posed in the Hadamard sense. By regularization techniques, it is possible to define the solution of the problem as the minimum of an energy function. To improve the quality of the reconstruction, some Boolean variables, associated with the discontinuities of the intensity color field, are introduced. Such variables, called line variables, have to be estimated and can be used in the energy function in an implicit way. Moreover, we impose that adjacent discontinuities have not to be parallel. To minimize the energy function, a CATILED (convex approximation technique for interacting line elements deblurring) algorithm is used. The experimental results confirm the good qualities of this technique.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"77 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":"127288919","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.2003.1234102
V. Bruni, D. Vitulano
An improvement of an interesting approach for denoising in the wavelet domain using an empirical Wiener filter (Choi, H. and Baraniuk, R., Proc. IEEE-SP Int. Symp. on Time-frequency and Time-scale Anal., 1998) is presented. It is based on a well-balanced matching of selection and attenuation performances using more than one wavelet basis. Experimental results are better than other wavelet-Wiener based techniques, both in terms of objective (signal-to-noise ratio, SNR) and subjective quality, requiring a moderate computing time.
利用经验维纳滤波器对小波域去噪的有趣方法进行改进(Choi, H.和Baraniuk, R.， Proc. IEEE-SP Int.)。计算机协会。时间-频率和时间尺度。， 1998)。它基于使用多个小波基的选择和衰减性能的良好平衡匹配。实验结果在客观(信噪比，SNR)和主观质量方面都优于其他基于小波维纳的技术，需要适度的计算时间。
{"title":"A Wiener filter improvement combining wavelet domains","authors":"V. Bruni, D. Vitulano","doi":"10.1109/ICIAP.2003.1234102","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234102","url":null,"abstract":"An improvement of an interesting approach for denoising in the wavelet domain using an empirical Wiener filter (Choi, H. and Baraniuk, R., Proc. IEEE-SP Int. Symp. on Time-frequency and Time-scale Anal., 1998) is presented. It is based on a well-balanced matching of selection and attenuation performances using more than one wavelet basis. Experimental results are better than other wavelet-Wiener based techniques, both in terms of objective (signal-to-noise ratio, SNR) and subjective quality, requiring a moderate computing time.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"58 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":"126302461","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.2003.1234121
L. Cordella, P. Foggia, Carlo Sansone, M. Vento
The paper presents a real-time speaker identification system based on the analysis of the audio track of a video stream. The system has been employed in the context of automatic video segmentation. It uses features evaluated in both the time and frequency domains. Their combined use significantly improve the performance of the system. Experiments have been carried on a database extracted from over one hour of television news, including 10 speakers. The obtained results confirm the effectiveness of the approach, showing an error rate less then 1% when the time interval used for identifying a speaker is about 1.5 seconds.
{"title":"A real-time text-independent speaker identification system","authors":"L. Cordella, P. Foggia, Carlo Sansone, M. Vento","doi":"10.1109/ICIAP.2003.1234121","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234121","url":null,"abstract":"The paper presents a real-time speaker identification system based on the analysis of the audio track of a video stream. The system has been employed in the context of automatic video segmentation. It uses features evaluated in both the time and frequency domains. Their combined use significantly improve the performance of the system. Experiments have been carried on a database extracted from over one hour of television news, including 10 speakers. The obtained results confirm the effectiveness of the approach, showing an error rate less then 1% when the time interval used for identifying a speaker is about 1.5 seconds.","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":"122138926","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.2003.1234124
M. Pietikäinen
Faces and hands recorded under natural environments are frequently subject to illumination variations which affect their color appearance. This is a problem when the color cue is used to detect skin candidates at pixel level. Traditionally, color constancy has been suggested for correction, but after a lot of effort no good solution suitable for machine vision has emerged. However, many approaches have been proposed for general skin detection, but they are typically tested under mild changes in illumination chromaticity or do not define the variation range. This makes it difficult to evaluate their applicability for objects under varying illumination. The paper compares four state-of-the-art skin detection schemes under realistic conditions with drastic chromaticity change.
{"title":"Detection of skin color under changing illumination: a comparative study","authors":"M. Pietikäinen","doi":"10.1109/ICIAP.2003.1234124","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234124","url":null,"abstract":"Faces and hands recorded under natural environments are frequently subject to illumination variations which affect their color appearance. This is a problem when the color cue is used to detect skin candidates at pixel level. Traditionally, color constancy has been suggested for correction, but after a lot of effort no good solution suitable for machine vision has emerged. However, many approaches have been proposed for general skin detection, but they are typically tested under mild changes in illumination chromaticity or do not define the variation range. This makes it difficult to evaluate their applicability for objects under varying illumination. The paper compares four state-of-the-art skin detection schemes under realistic conditions with drastic chromaticity change.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"21 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":"114609052","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.2003.1234033
L. Marchesotti, S. Piva, C. Regazzoni
This paper presents an agent-based architecture designed to functionally combine data from an homogeneous network of sensors for tracking purposes. The system has been developed in a video surveillance context to detect, classify and track moving objects in a scene of interest. Although single camera systems could perform the tasks outlined above, they would not be able to deal with topologically complex environments such as corridor, corners and indoor locations in general. The multi-sensor approach has been used to overcome these problems, nevertheless issues arise such as data fusion, synchronization and camera calibration. The sensor fusion approach here purposed uses autonomous software agents to negotiate the combination of data and the fusion is carried out by appropriate signal processing algorithms. The system has been tested with indoor video sequences to show the system's ability to preserve identity and of correct trajectory estimation of the tracked object.
{"title":"An agent-based approach for tracking people in indoor complex environments","authors":"L. Marchesotti, S. Piva, C. Regazzoni","doi":"10.1109/ICIAP.2003.1234033","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234033","url":null,"abstract":"This paper presents an agent-based architecture designed to functionally combine data from an homogeneous network of sensors for tracking purposes. The system has been developed in a video surveillance context to detect, classify and track moving objects in a scene of interest. Although single camera systems could perform the tasks outlined above, they would not be able to deal with topologically complex environments such as corridor, corners and indoor locations in general. The multi-sensor approach has been used to overcome these problems, nevertheless issues arise such as data fusion, synchronization and camera calibration. The sensor fusion approach here purposed uses autonomous software agents to negotiate the combination of data and the fusion is carried out by appropriate signal processing algorithms. The system has been tested with indoor video sequences to show the system's ability to preserve identity and of correct trajectory estimation of the tracked object.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"30 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":"114863124","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.2003.1234039
H. Eng, A. H. Kam, Junxian Wang, W. Yau, Lijuan Jiang
Many deployed systems for human motion tracking and detection are found inadequate when applied on hostile outdoor environments. This paper provides insights into this problem by developing an outdoor aquatic surveillance system, which detects swimmers within the hostile environment of an outdoor public swimming pool. A novel block-based background model and thresholding-with-hysteresis methodology is proposed to extract swimmers amid reflections, ripples, splashes and lighting changes. The problem of partial occlusion between swimmers is resolved based on a proposed Markov random field framework. The algorithm has been incorporated into a live system with robust results for different challenging outdoor pool conditions.
{"title":"Human detection and tracking within hostile aquatic environments","authors":"H. Eng, A. H. Kam, Junxian Wang, W. Yau, Lijuan Jiang","doi":"10.1109/ICIAP.2003.1234039","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234039","url":null,"abstract":"Many deployed systems for human motion tracking and detection are found inadequate when applied on hostile outdoor environments. This paper provides insights into this problem by developing an outdoor aquatic surveillance system, which detects swimmers within the hostile environment of an outdoor public swimming pool. A novel block-based background model and thresholding-with-hysteresis methodology is proposed to extract swimmers amid reflections, ripples, splashes and lighting changes. The problem of partial occlusion between swimmers is resolved based on a proposed Markov random field framework. The algorithm has been incorporated into a live system with robust results for different challenging outdoor pool conditions.","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":"116874150","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.2003.1234107
M. R. Hamid, Aijaz A. Baloch, A. Bilal, Nauman Zaffar
This paper presents a new technique to segment objects of interest from cluttered background with varying edge densities and illumination conditions from gray scale imagery. An optimal background model is generated and an index of disparity of the objects from this model is computed. This index estimates the disparity, both in terms of edge densities and edge orientation. We introduce feature based conditional morphology to process the representations that are most likely to belong to the object of interest and obtain a distilled edge map. These edges are linked using N/sup th/ order interpolation to get the final outline of the object. We compare our approach with 9 contemporary background subtraction algorithms (Toyama et al. (1999)). Our approach shows significant performance advantages and uses only the gray scale images, while the other approaches also need the color images for their algorithms. A comparison with the conventional morphological techniques is also made to highlight the advantages of our algorithms.
提出了一种从灰度图像中具有不同边缘密度和光照条件的杂乱背景中分割感兴趣目标的新技术。生成最优背景模型，并以此模型计算出目标的视差指数。该指数从边缘密度和边缘方向两方面来估计差异。我们引入基于特征的条件形态学来处理最有可能属于感兴趣对象的表示，并获得一个蒸馏的边缘映射。使用N/sup /阶插值将这些边连接起来，以获得对象的最终轮廓。我们将我们的方法与9种当代背景减法算法(Toyama et al.(1999))进行了比较。我们的方法显示出明显的性能优势，并且只使用灰度图像，而其他方法的算法也需要彩色图像。并与传统形态学技术进行了比较，以突出我们的算法的优势。
{"title":"Object segmentation using feature based conditional morphology","authors":"M. R. Hamid, Aijaz A. Baloch, A. Bilal, Nauman Zaffar","doi":"10.1109/ICIAP.2003.1234107","DOIUrl":"https://doi.org/10.1109/ICIAP.2003.1234107","url":null,"abstract":"This paper presents a new technique to segment objects of interest from cluttered background with varying edge densities and illumination conditions from gray scale imagery. An optimal background model is generated and an index of disparity of the objects from this model is computed. This index estimates the disparity, both in terms of edge densities and edge orientation. We introduce feature based conditional morphology to process the representations that are most likely to belong to the object of interest and obtain a distilled edge map. These edges are linked using N/sup th/ order interpolation to get the final outline of the object. We compare our approach with 9 contemporary background subtraction algorithms (Toyama et al. (1999)). Our approach shows significant performance advantages and uses only the gray scale images, while the other approaches also need the color images for their algorithms. A comparison with the conventional morphological techniques is also made to highlight the advantages of our algorithms.","PeriodicalId":218076,"journal":{"name":"12th International Conference on Image Analysis and Processing, 2003.Proceedings.","volume":"29 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":"117275277","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：