Nicola Adami

State-of-the-Art and Trends in Scalable Video Compression With Wavelet-Based Approaches

Scalable video coding (SVC) differs form traditional single point approaches mainly because it allows to encode in a unique bit stream several working points corresponding to different quality, picture size and frame rate. This work describes the current state-of-the-art in SVC, focusing on wavelet based motion-compensated approaches (WSVC). It reviews individual components that have been designed to address the problem over the years and how such components are typically combined to achieve meaningful WSVC architectures. Coding schemes which mainly differ from the space-time order in which the wavelet transforms operate are here compared, discussing strengths and weaknesses of the resulting implementations. An evaluation of the achievable coding performances is provided considering the reference architectures studied and developed by ISO/MPEG in its exploration on WSVC. The paper also attempts to draw a list of major differences between wavelet based solutions and the SVC standard jointly targeted by ITU and ISO/MPEG. A major emphasis is devoted to a promising WSVC solution, named STP-tool, which presents architectural similarities with respect to the SVC standard. The paper ends drawing some evolution trends for WSVC systems and giving insights on video coding applications which could benefit by a wavelet based approach.

Two-layer coding algorithm for high dynamic range images based on luminance compensation

A two-layer coding algorithm for high dynamic range images is discussed. In the first layer, a low dynamic range image is encoded by a conventional codec, and then the residual information that represents the difference between an original and the decoded images in the first layer is encoded in the second layer, which realizes compatibility with conventional image file formats. Our method utilizes the approximation of an inverse tone mapping function that reduces the high dynamic range to a displayable range. Our algorithm significantly improves a compression performance, compared to conventional methods.

High Dynamic Range Image Watermarking Robust Against Tone-Mapping Operators

High dynamic range (HDR) images represent the future format for digital images since they allow accurate rendering of a wider range of luminance values. However, today special types of preprocessing, collectively known as tone-mapping (TM) operators, are needed to adapt HDR images to currently existing displays. Tone-mapped images, although of reduced dynamic range, have nonetheless high quality and hence retain some commercial value. In this paper, we propose a solution to the problem of HDR image watermarking, e.g., for copyright embedding, that should survive TM. Therefore, the requirements imposed on the watermark encompass imperceptibility, a certain degree of security, and robustness to TM operators. The proposed watermarking system belongs to the blind, detectable category; it is based on the quantization index modulation (QIM) paradigm and employs higher order statistics as a feature. Experimental analysis shows positive results and demonstrates the system effectiveness with current state-of-art TM algorithms.

XKin: an open source framework for hand pose and gesture recognition using kinect

This work targets real-time recognition of both static hand-poses and dynamic hand-gestures in a unified open-source framework. The developed solution enables natural and intuitive hand-pose recognition of American Sign Language (ASL), extending the recognition to ambiguous letters not challenged by previous work. While hand-pose recognition exploits techniques working on depth information using texture-based descriptors, gesture recognition evaluates hand trajectories in the depth stream using angular features and hidden Markov models (HMM). Although classifiers come already trained on ASL alphabet and 16 uni-stroke dynamic gestures, users are able to extend these default sets by adding their personalized poses and gestures. The accuracy and robustness of the recognition system have been evaluated using a publicly available database and across many users. The XKin open project is available online (Pedersoli, XKin libraries. https://github.com/fpeder/XKin, 2013) under FreeBSD License for researchers in human–machine interaction.

Generating story variants with constrained video recombination

We present a novel approach to the automatic generation of filmic variants within an implemented Video-Based Storytelling (VBS) system that successfully integrates video segmentation with stochastically controlled re-ordering techniques and narrative generation via AI planning. We have introduced flexibility into the video recombination process by sequencing video shots in a way that maintains local video consistency and this is combined with exploitation of shot polysemy to enable shot reuse in a range of valid semantic contexts. Results of evaluations on output narratives using a shared set of video data show consistency in terms of local video sequences and global causality with no loss of generative power.

The ToCAI Description Scheme for Indexing and Retrieval of Multimedia Documents

A framework, called Table of Content-Analytical Index (ToCAI), for the content description of multimedia material is presented. The idea for such a description scheme (DS) comes out from the structures used for indexing technical books (containing a Table of Content, typically placed at the beginning of the book, where the list of topics is organized hierarchically into chapters, sections, and an Analytical Index, typically placed at the end of the book, where keywords are listed alphabetically). The ToCAI description scheme provides similarly a hierarchical description of the time sequential structure of a multimedia document (ToC), suitable for browsing, and an “Analytical Index” (AI) of audio-visual key items for the document, suitable for effective retrieval. Besides two other sub-description schemes are proposed to specify the program category and the description of other metadata associated to the multimedia document in the general DS. The detailed structure of the DS is presented by means of a UML diagram. Moreover, some suitable automatic extraction methods for the identification of the values associated to the descriptors that compose the ToCAI are presented and discussed. Finally, a browsing application example is also proposed.

New local tone mapping and two-layer coding for HDR images

This paper proposes a two-layer High Dynamic Range (HDR) coding scheme using a new tone mapping. Our tone mapping method transforms an HDR image onto a Low Dynamic Range (LDR) image by using a base map that is a smoothed version of the HDR luminance. In our scheme, the HDR image can be reconstructed from the tone mapped LDR image. Our method makes use of this property to realize a two-layer HDR coding by encoding both of the tone mapped LDR image and the base map. This paper validates its effectiveness of our approach through some experiments.

XKin -: eXtendable hand pose and gesture recognition library for kinect

In this work we provide an open-source framework for Kinect enabling more natural and intuitive hand-gesture communication between human and computer devices. The software package is endowed with useful tools for training the system to work with user-defined postures and gestures. The XKin project is fully implemented in C and freely available at https://github.com/fpeder/XKin under FreeBSD License. Our goal is to encourage contributions from other researchers and developers in building an open and effective system for empowering a natural modality for human-machine interaction.

High Dynamic Range image tone mapping based on local Histogram Equalization

High Dynamic Range (HDR) images can represent the acquired scene with a greater dynamic range of luminance than classical Low Dynamic Range (LDR) ones. Despite the recent diffusion of some HDR camera models, HDR displays are not yet in the market. For this reason HDR images need to be adapted in order to be properly rendered through conventional devices. This operation mainly consists in a dynamic range compression realized by applying a Tone Mapping Operator (TMO). In this work, a new tone map algorithm, derived from the Contrast Limited Adaptive Histogram Equalization (CLAHE) technique, is presented. With respect to the original CLAHE, in the proposed implementation an adaptive contrast limit and a new strategy for the determination of local tone mapping functions have been introduced. The comparison between the obtained LDR images, and those produced by applying State of the Art TMOs, evidences how the main characteristic of the proposed algorithm is the ability to equally enhance visibility in both dark and bright areas. This could be, for example, a key feature in video surveillance applications and automotive safety camera systems.

Markers of unsustainable gambling for early detection of at-risk online gamblers

In this work we propose novel markers for identifying at-risk gamblers based on the concept of sustainability. The first hypothesis here verified is that problematic gamblers oscillate between intervals of increasing wager size followed by rapid drops, probably because they exceed their economic sustainability limits. Due to the non-periodic nature of these fluctuations, the proposed marker detects a certain occurring feature, such as a rapid drop in wager size, over a wide range of fluctuation periods, drop sizes and shapes. The second marker, counting the number of games the gambler is involved in, aims at predicting possible consequences of an exceeding amount of time dedicated to gambling, that ultimately causes social and relational breakdowns. In the experimental phase we demonstrate how the adoption of these markers allows for identifying larger segments of high- and medium-risk gamblers with respect to previous research on actual betting behaviours.