{"title":"Region Based Image Indexing and Retrieval Inspired by Text Search","authors":"Giuseppe Amato, V. Magionami, P. Savino","doi":"10.1109/ICIAPW.2007.37","DOIUrl":"https://doi.org/10.1109/ICIAPW.2007.37","url":null,"abstract":"In this paper we present an approach for image similarity search that takes inspiration from text retrieval. Images are indexed using visual terms chosen from a visual lexicon. Each visual term represents a typology of visual regions, according to various criteria. The visual lexicon is obtained by analyzing a training set of images, to infer which are the relevant typology of visual regions. We have defined a weighting and matching schema that are able respectively to associate visual terms with images and to compare images by means of the associated terms. We show that the proposed approach do not lose performance, in terms of effectiveness, with respect to other methods existing in literature, and at the same time offers higher performance, in terms of efficiency, given the possibility of using inverted files to support similarity searching. The proposed techniques were implemented in a running prototype.","PeriodicalId":114866,"journal":{"name":"14th International Conference of Image Analysis and Processing - Workshops (ICIAPW 2007)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124991093","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}
A. Smeulders, J. V. Van Gemert, B. Huumink, D. Koelma, O. de Rooij, K. V. D. Van De Sande, C. Snoek, C. Veenman, M. Worring
{"title":"Semantic Video Search","authors":"A. Smeulders, J. V. Van Gemert, B. Huumink, D. Koelma, O. de Rooij, K. V. D. Van De Sande, C. Snoek, C. Veenman, M. Worring","doi":"10.1109/ICIAPW.2007.39","DOIUrl":"https://doi.org/10.1109/ICIAPW.2007.39","url":null,"abstract":"In this paper we describe the current performance of our MediaMill system as presented in the TRECVID 2006 benchmark for video search engines. The MediaMill team participated in two tasks: concept detection and search. For concept detection we use the MediaMill Challenge as experimental platform. The MediaMill Challenge divides the generic video indexing problem into a visual-only, textual- only, early fusion, late fusion, and combined analysis experiment. We provide a baseline implementation for each experiment together with baseline results. We extract image features, on global, regional, and keypoint level, which we combine with various supervised learners. A late fusion approach of visual-only analysis methods using geometric mean was our most successful run. With this run we conquer the Challenge baseline by more than 50%. Our concept detection experiments have resulted in the best score for three concepts: i.e. desert, flag us, and charts. What is more, using LSCOM annotations, our visual-only approach generalizes well to a set of 491 concept detectors. To handle such a large thesaurus in retrieval, an engine is developed which allows users to select relevant concept detectors based on interactive browsing using advanced visualizations. Similar to previous years our best interactive search runs yield top performance, ranking 2nd and 6th overall.","PeriodicalId":114866,"journal":{"name":"14th International Conference of Image Analysis and Processing - Workshops (ICIAPW 2007)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116037658","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":"A System for the Automatic Identification of Music Works","authors":"N. Orio","doi":"10.1109/ICIAPW.2007.9","DOIUrl":"https://doi.org/10.1109/ICIAPW.2007.9","url":null,"abstract":"This paper describes a system able to identify a music work through the analysis of the audio recording of a performance. The approach is based on the statistical modeling of the expected audio features of music performances, given a database of known music works. In particular, the automatic identification is based on an application of hidden Markov models (HHMs), which are automatically built from music scores available in digital format. States of the HMMs are labeled by score events, and transition and observation probabilities are directly computed from the information on the score. Three alternative approaches to the identification task have been proposed and tested on a set of audio excerpts. Results showed that the methodology can achieve satisfactory results. A prototype system has been developed, and will be demonstrated, which allows in a few seconds to identify an unknown recording from a dataset of hundreds of scores.","PeriodicalId":114866,"journal":{"name":"14th International Conference of Image Analysis and Processing - Workshops (ICIAPW 2007)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122616300","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":"Combining Strategies for Automatic White Estimation in Real Images","authors":"S. Bianco, F. Gasparini, R. Schettini","doi":"10.1109/ICIAPW.2007.19","DOIUrl":"https://doi.org/10.1109/ICIAPW.2007.19","url":null,"abstract":"In this paper we consider combining strategies of several white balance algorithms available in the literature to improve the illuminant chromaticity estimation and correction for digital images. We have tested and compared the original algorithms and the combining strategies on three databases of carefully controlled real data, composed respectively of multispectral CFA and RGB images. The experimental results, evaluated using the Wilcoxon Sign Test, are reported and commented.","PeriodicalId":114866,"journal":{"name":"14th International Conference of Image Analysis and Processing - Workshops (ICIAPW 2007)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133611900","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":"Semantics Driven Resampling of the OSA-UCS","authors":"G. Menegaz, A. Le Troter, J. Boi, J. Sequeira","doi":"10.1109/ICIAPW.2007.41","DOIUrl":"https://doi.org/10.1109/ICIAPW.2007.41","url":null,"abstract":"In this paper, we propose a resampling of the OSA-UCS. Following the same sampling criterion that used to define the 424 specimens of the OSA-UCS set, we enlarged such an ensemble by adding 590 samples located in the outer region of the original volume. This allows to overcome the bottleneck in the use of the original color basis for computer vision applications due to lack of saturated colors. The outcomes of a color categorization experiment performed on the extended basis were used to train a discrete color naming model that we have recently proposed. The model was validated through the analysis of its performance for segmenting natural images. Results show that the extended basis removes the inability of the model to deal with saturated colors which significantly improves segmentation results and makes the extended bases exploitable for computer vision applications.","PeriodicalId":114866,"journal":{"name":"14th International Conference of Image Analysis and Processing - Workshops (ICIAPW 2007)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114801423","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}
R. Neumayer, J. Frank, P. Hlaváč, T. Lidy, A. Rauber
{"title":"Bringing Mobile Map-Based Access to Digital Audio to the End User","authors":"R. Neumayer, J. Frank, P. Hlaváč, T. Lidy, A. Rauber","doi":"10.1109/ICIAPW.2007.14","DOIUrl":"https://doi.org/10.1109/ICIAPW.2007.14","url":null,"abstract":"Private as well as commercial music collections keep growing in size and diversity. With an increasing number of tracks and the resulting complexity users quickly face proplems in handling their collections in an adequate way. At the same time, new business models of online vendors arise and the inherent industry interest in new ways of distribution channels and devices becomes immanent. In this paper, we show alternative ways of interacting with large music collections, based on the Self-Organising Map clustering algorithm applied to an audio feature representation of audio files. We therein focus on the presentation of full desktop applications as well as applications for mobile devices like PDAs and Smartphones with the goal of bringing Music Information Retrieval technologies closer to end users. Further, the presented interfaces give an outlook to means of access to other types of media in streaming environments, e.g. video.","PeriodicalId":114866,"journal":{"name":"14th International Conference of Image Analysis and Processing - Workshops (ICIAPW 2007)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121524613","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":"Animation Movie Abstraction: Key Frame Adaptative Selection Based on Color Histogram Filtering","authors":"L. Ott, P. Lambert, B. Ionescu, D. Coquin","doi":"10.1109/ICIAPW.2007.12","DOIUrl":"https://doi.org/10.1109/ICIAPW.2007.12","url":null,"abstract":"This paper deals with the construction of animation movie abstracts. The proposed video abstracts are computed using an adaptive selection of key frames obtained by color histogram analysis. The method exhibits three main parts. In the first step, a shot detection is performed. Then, within each shot, an adaptive number of key frames is selected. This selection is performed by analyzing cumulative distances between frame color histograms. In the third step, an inter-shot examination is performed. Using an iterative selection we provide a user-specified number of movie representative frames. The method has been tested on a database from the International Animated Film Festival that takes place yearly in Annecy.","PeriodicalId":114866,"journal":{"name":"14th International Conference of Image Analysis and Processing - Workshops (ICIAPW 2007)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122581598","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 Constancy by Local Averaging","authors":"A. Gijsenij, T. Gevers","doi":"10.1109/ICIAPW.2007.16","DOIUrl":"https://doi.org/10.1109/ICIAPW.2007.16","url":null,"abstract":"As the color of an object partly depends on the color of the illumination, computer vision systems that rely on color features are likely to benefit from a property that most humans have naturally: color constancy. Color constancy is the ability to recognize colors of objects, invariant to the color of the light source. In this paper, an new algorithm is proposed based on local averaging, which is tested on a publicly available data set. The proposed method is shown to be at least competitive to current state-of-the-art methods, however, at lower computational costs.","PeriodicalId":114866,"journal":{"name":"14th International Conference of Image Analysis and Processing - Workshops (ICIAPW 2007)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116291981","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":"Safe Red-Eye Correction Plug-in Using Adaptive Methods","authors":"L. Marchesotti, G. Csurka, M. Bresssan","doi":"10.1109/ICIAPW.2007.38","DOIUrl":"https://doi.org/10.1109/ICIAPW.2007.38","url":null,"abstract":"An important issue with red-eye correction is that it might result in image degradation. This can be due to the detection of false positives or, even in the case of correct detection, to an inadequate correction technique. Three correction methods are proposed and compared according to their image degradation risk and their expected perceptual quality improvement. Based on those analyses an adaptive system is designed which selects the correction strategy dependent on those measures and the detection confidence. Finally, both qualitative (visual preferences) and quantitative (pixel counts on manual segmented images) evaluation results are shown.","PeriodicalId":114866,"journal":{"name":"14th International Conference of Image Analysis and Processing - Workshops (ICIAPW 2007)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116883583","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. Urruty, Stanislas Lew, Nacim Ihaddadene, D. Simovici
{"title":"Detecting Eye Fixations by Projection Clustering","authors":"T. Urruty, Stanislas Lew, Nacim Ihaddadene, D. Simovici","doi":"10.1145/1314303.1314308","DOIUrl":"https://doi.org/10.1145/1314303.1314308","url":null,"abstract":"The identification of the components of eye movements (fixations and saccades) is an essential part in the analysis of visual behavior because these types of movements provide the basic elements used by further investigations of human vision. However, many of the algorithms that detect fixations present some problems (consistency, robustness, many input parameters). In this article we present a new eye fixation identification technique that is based on clustering of eye positions using projections and projection aggregation.","PeriodicalId":114866,"journal":{"name":"14th International Conference of Image Analysis and Processing - Workshops (ICIAPW 2007)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134274647","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}