01961nas a2200169   4500008004100000245006900041210006700110260000900177300001200186490000600198520140100204653001801605653002301623100001401646700001401660856011701674       2010                        eng d00aContent-based image retrieval systems-reviewing and benchmarking0 aContentbased image retrieval systemsreviewing and benchmarking  c2010  a54 - 640 v83 aThe last detailed review of Content-based Image Retrieval Systems (CBIRS) is that from Veltkamp and Tanase [VT02], updated in 2002. Since then, many new systems emerged, other systems were improved, but many systems are no longer supported. This paper reconsiders the systems described by Veltkamp and Tanase and proposes in addition for a selection of existing CBIRS a quantitative comparison. For this purpose we developed a benchmarking system for CBIRS based on how accurate they could match ideal (ground truth) results. As measure we introduced the RankWRN , which we developed based on the Normalized Avarage Rank. Our measure allows fair and accurate comparisons (due to multiple similarity values) of different CBIRS with respect to different queries. None of the other benchmarks allow this comparison. The choice for a system to be compared quantitatively was motivated by availability of the source or runtime code and the liveness (i.e., active development on the CBIRS). The benchmarked systems were SIMBA, SIMPLIcity, PictureFinder, ImageFinder, Caliph&amp;, VIPER/GIFT and Oracle Intermedia. Results show that VIPER/GIFT performs best in the settings of our benchmark, Caliph&amp; is second and SIMBA third. The default parameter settings of the systems tend to show the best results. MPEG-7 descriptors, which are used in Caliph&amp;, show a good performance in the benchmarking.10aImage ranking10aMPEG-7 descriptors1 aKosch, H.1 aMaier, P.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-77958035095&partnerID=40&md5=3332d95bebdc7fdabeda9f57902ea60801735nas a2200205   4500008004100000245007900041210006900120260000900189300001200198490000600210520104200216653002201258653001901280653002301299653003301322100001701355700002001372700002001392856011701412       2007                        eng d00aAnalysis of the data quality of audio descriptions of environmental sounds0 aAnalysis of the data quality of audio descriptions of environmen  c2007  a48 - 540 v53 aIn this paper we perform statistical data analysis of a broad set of state-of-the-art audio features and low-level MPEG-7 audio descriptors. The investigation comprises data analysis to reveal redundancies between state-of-the-art audio features and MPEG-7 audio descriptors. We introduce a novel measure to evaluate the information content of a descriptor in terms of variance. Statistical data analysis reveals the amount of variance contained in a feature. It enables identification of independent and redundant features. This approach assists in efficient selection of orthogonal features for content-based retrieval. We believe that a good feature should provide descriptions with high variance for the underlying data. Combinations of features should consist of decorrelated features in order to increase expressiveness of the descriptions. Although MPEG-7 is a popular and widely used standard for multimedia description, only few investigations do exist that address analysis of the data quality of low-level MPEG-7 descriptions.10aAudio descriptors10aAudio features10aMPEG-7 descriptors10aMultimedia content retrieval1 aMitrovic, D.1 aZeppelzauer, M.1 aEidenberger, H.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-44849119790&partnerID=40&md5=8ed62cb5e71bdeccf00462d93d30e2db