Guest Editorial: Special Issue on Recent Advances in Content Analysis for Media Computing

Kim-Hui Yap, Lap-Pui Chau, Kap-Luk Chan
2009 Journal of Signal Processing Systems  
This special issue consists of extended papers selected from the 2007 International Conference on Information, Communications and Signal Processing (ICICS07). ICICS07 was held in Singapore in December 2007, and it received a positive response from the research communities with more than 700 paper submissions. The papers in this special issue are selected based on their ICICS07 reviews, their relevance to content analysis for media computing, and the timeliness of the research. The volume of
more » ... a data (image, video, audio, etc.) has grown tremendously in recent years due to increasing popularity of consumer electronics products such as video camera, prevalence of low-cost high-capacity storage devices, and the increasing proliferation of media data over the Internet and wireless networks. Coupled with the rapidly improving wired and wireless network infrastructure, the demand for intelligent and efficient solutions in media creation, indexing, search, transmission and display is fast growing. This special issue aims to present some recent advances in content analysis for media computing. In particular, it will focus on the following topics: (i) image indexing and retrieval, (ii) video search and classification, and (iii) a combination of works involving audio processing, hand sign understanding and visual quality assessment of videos. This special issue contains two papers that present some recent advances in image indexing and retrieval. The paper "A review of region-based image retrieval" provides an indepth survey of various conventional and state-of-the-art region-based image retrieval algorithms. As opposed to the global-based approaches, region-based techniques partition an image into different image regions and extract various visual features from these regions to represent them. The paper focuses in particular on three issues: (a) local regionbased features, (b) similarity measures, and (c) relevance feedback based on regions. In the paper "Knowledge propagation in collaborative tagging for image retrieval", a new knowledge propagation scheme that propagates keywords from a subset of annotated images to the unannotated ones is proposed. The method is based on content analysis of images and training of keyword classifiers. The salient regions of the images are determined and their importance is estimated using support vector machine (SVM). Once the previously unannotated images are tagged with propagated keywords, text-based image search can then be performed. Video search and classification is another important field in media content analysis. As opposed to the image data, videos contain temporal information and they consist of audio and visual components. Therefore, video search and classification methods need to fully utilize this information. This special issue comprises two papers on video search and classification. Together, they explore how effective audio and visual features can be combined to represent a video and how user interaction can be integrated to improve the performance of video search. In the paper "A new learning algorithm for the fusion of adaptive audio-visual features for the retrieval and classification of movie clips", a new learning algorithm for audio-visual fusion is proposed. The developed system utilizes perceptual features for content characterization. An adaptive video indexing scheme is used to represent the visual feature, while a
doi:10.1007/s11265-009-0433-5 fatcat:snvjjbrtcfad3kn6psioj4b3fa