Janko Calic

Efficient Layout of Comic-Like Video Summaries

In order to represent large amounts of information in the form of a video key-frame summary, this paper studies narrative grammar of comics, and using its universal and intuitive rules, lays out visual summaries in an efficient and user centered way. The system ranks importance of key-frame sizes in the final layout by balancing the dominant visual representability and discovery of unanticipated content utilizing a specific cost function and an unsupervised robust spectral clustering technique. A final layout is created using an optimization algorithm based on dynamic programming. Algorithm efficiency and robustness are demonstrated by comparing the results with the optimal panelling solutions.

Efficient key-frame extraction and video analysis

Content-based video indexing and retrieval has its foundations in the analyses of the prime video temporal structures. Consequently, technologies for video segmentation and key-frame extraction have become crucial for the development of advanced digital video systems. Conventional algorithms for video partitioning and key-frame extraction are mainly implemented autonomously. By focusing the analysis on compressed video features, this paper introduces a real-time algorithm for scene change detection and key-frame extraction that generates frame difference metrics by analysing the statistics of the macro-block features extracted from an MPEG compressed stream. The key-frame extraction method is implemented using difference metrics in curve simplification by means of a discrete contour evolution algorithm. This approach resulted in a fast and robust algorithm. Results of computer simulations are reported.

A Survey on Multimodal Video Representation for Semantic Retrieval

This paper surveys the approaches to video representation, focusing on semantic analysis for content-based indexing and retrieval. A problem of adaptive representation of digital multimedia is critically assessed and some novel ideas are presented. Furthermore, the concept of video multimodality is reevaluated and redefined in order to introduce modalities such as editing technique or affect to the audience

Temporal segmentation of MPEG video streams

Many algorithms for temporal video partitioning rely on the analysis of uncompressed video features. Since the information relevant to the partitioning process can be extracted directly from the MPEG compressed stream, higher efficiency can be achieved utilizing information from the MPEG compressed domain. This paper introduces a real-time algorithm for scene change detection that analyses the statistics of the macroblock features extracted directly from the MPEG stream. A method for extraction of the continuous frame difference that transforms the 3D video stream into a 1D curve is presented. This transform is then further employed to extract temporal units within the analysed video sequence. Results of computer simulations are reported.

A multiresolution technique for video indexing and retrieval

This paper presents a novel approach to multiresolution analysis and scalability in video indexing and retrieval. A scalable algorithm for video parsing and key-frame extraction is introduced. The technique is based on real-time analysis of MPEG motion variables and scalable metrics simplification by discrete contour evolution. Furthermore, a hierarchical key-frame retrieval method using scalable colour histogram analysis is presented. It offers customisable levels of detail in the descriptor space, where the relevance order is determined by degradation of the image, and not by degradation of the image histogram. To assess the performance of the approach, several experiments have been conducted. Selected results are reported.

Temporal video segmentation for real-time key frame extraction

The extensive amount of media coverage today, generates difficulties in identifying and selecting desired information. Browsing and retrieval systems become more and more necessary in order to support users with powerful and easy-to-use tools for searching, browsing and summarization of information content. The starting point for these tasks in video browsing and retrieval systems is the low level analysis of video content, especially the segmentation of video content into shots. This paper presents a fast and efficient way to detect shot changes using only the temporal distribution of macroblock types in MPEG compressed video. The notion of a dominant reference frame is introduced here. A dominant frame denotes the reference frame (I or P) used as prediction reference for most of the macroblocks from a subsequent B frame.

ICBR - Multimedia Management System for Intelligent Content Based Retrieval

This paper presents a system designed for the management of multimedia databases that embarks upon the problem of efficient media processing and representation for automatic semantic classification and modelling. Its objectives are founded on the integration of a large-scale wildlife digital media archive with a manually annotated semantic metadata organised in a structured taxonomy and media classification system. Novel techniques will be applied to temporal analysis, intelligent key-frame extraction, animal gait analysis, semantic modelling and audio classification. The system demonstrator will be developed as a part of an ICBR project within the 3C Research programme of convergent technology research for digital media processing and communications.

FreeEye: interactive intuitive interface for large-scale image browsing

Intuitive interfaces have become increasingly important multimedia applications, from personal photo collection to professional management systems. This paper presents a novel intuitive interactive interface for browsing of large image collections that visualizes underlying structure of the dataset by its size and spatial relations. In order to achieve this, images are initially clustered using an unsupervised graph-based clustering algorithm. By selecting images in a hierarchical layout of the screen, user can intuitively navigate through the collection. The experimental results demonstrate a significant speed-up in a content search scenario compared to a standard browsing interface, as well as inherent intuitiveness of the system.

Compact visualisation of video summaries

This paper presents a system for compact and intuitive video summarisation aimed at both high-end professional production environments and small-screen portable devices. To represent large amounts of information in the form of a video key-frame summary, this paper studies the narrative grammar of comics, and using its universal and intuitive rules, lays out visual summaries in an efficient and user-centered way. In addition, the system exploits visual attention modelling and rapid serial visual presentation to generate highly compact summaries on mobile devices. A robust real-time algorithm for key-frame extraction is presented. The system ranks importance of key-frame sizes in the final layout by balancing the dominant visual representability and discovery of unanticipated content utilising a specific cost function and an unsupervised robust spectral clustering technique. A final layout is created using an optimisation algorithm based on dynamic programming. Algorithm efficiency and robustness are demonstrated by comparing the results with a manually labelled ground truth and with optimal panelling solutions.

Stereoscopic Video Quality Assessment Using Binocular Energy

Stereoscopic imaging is becoming increasingly popular. However, to ensure the best quality of experience, there is a need to develop more robust and accurate objective metrics for stereoscopic content quality assessment. Existing stereoscopic image and video metrics are either extensions of conventional 2-D metrics (with added depth or disparity information) or are based on relatively simple perceptual models. Consequently, they tend to lack the accuracy and robustness required for stereoscopic content quality assessment. This paper introduces full-reference stereoscopic image and video quality metrics based on a human visual system (HVS) model incorporating important physiological findings on binocular vision. The proposed approach is based on the following three contributions. First, it introduces a novel HVS model extending previous models to include the phenomena of binocular suppression and recurrent excitation. Second, an image quality metric based on the novel HVS model is proposed. Finally, an optimized temporal pooling strategy is introduced to extend the metric to the video domain. Both image and video quality metrics are obtained via a training procedure to establish a relationship between subjective scores and objective measures of the HVS model. The metrics are evaluated using publicly available stereoscopic image/video databases as well as a new stereoscopic video database. An extensive experimental evaluation demonstrates the robustness of the proposed quality metrics. This indicates a considerable improvement with respect to the state-of-the-art with average correlations with subjective scores of 0.86 for the proposed stereoscopic image metric and 0.89 and 0.91 for the proposed stereoscopic video metrics.