Multiple Description Coding and Recovery of Free Viewpoint Video for Wireless Multi-Path Streaming

By transmitting texture and depth videos captured from two nearby camera viewpoints, a client can synthesize via depth-image-based rendering (DIBR) any freely chosen intermediate virtual view of the 3D scene, enhancing the user’s perception of depth. During wireless network transmission, burst packet losses can corrupt the transmitted texture and depth videos and degrade the synthesized view quality at the client. In this paper, we propose a multiple description coding system for multi-path transmission of free-viewpoint video, with joint interview and temporal description recovery capability. In particular, we encode separately the even frames of the left view and the odd frames of the right view, and transmit them as one description on one path. The second description comprises the remaining frames in the two views and is transmitted over a second path. If the receiver receives only one description due to burst loss in the other path, the missing frames in the other description are partially reconstructed using our frame recovery procedure.

First, we construct two recovery candidates for each lost pixel in a frame. The first candidate is generated via temporal super-resolution from its predecessor and successor frames in the same view. The second candidate is generated via DIBR from the received frame of the same time instance in the other view. Next, we select the best pixel candidates one patch at a time, where an image patch corresponds to a neighborhood of pixels with similar depth values in the 3D scene. Near-optimal source and channel coding rates for each description are selected using a branch-and-bound method, for given transmission bandwidth on each path. Experimental results show that our system can outperform a traditional single-description/single-path transmission scheme by up to 5.5 dB in Peak Signal-to-Noise Ratio (PSNR) of the synthesized intermediate view at the client.

A tunable data hiding scheme for CABAC in H.264/AVC video streams

In this paper, a new method for tunable data hiding in H.264/AVC streams is presented. In order to provide the greatest flexibility for users with varying requirement, a simple control operation for capacity of hiding secret message is proposed.

One group of coefficients chosen from specific macro block is used to accommodate the secret message bits. Based on experimental results, the proposed scheme has been verified that a higher hiding capacity can be obtained at lower degradation on the bit rate and peak signal-to-noise ratio.

Decoding Semantics Categorization during Natural Viewing of Video Streams

Exploring the functional mechanism of the human brain during semantics categorization and subsequently leverage current semantics-oriented multimedia analysis by functional brain imaging have been receiving great attention in recent years. In the field, most of existing studies utilized strictly controlled laboratory paradigms as experimental settings in brain imaging data acquisition. They also face the critical problem of modeling functional brain response from acquired brain imaging data. In this paper, we present a brain decoding study based on sparse multi-nominal logistic regression (SMLR) algorithm to explore the brain regions and functional interactions during semantics categorization. The setups of our study are two folds.

First, we use naturalistic video streams as stimuli in functional magnetic resonance imaging (fMRI) to simulate the complex environment for semantics perception that the human brain has to process in real life. Second, we model brain responses to semantics categorization as functional interactions among large-scale brain networks. Our experimental results show that semantics categorization can be accurately predicted by both intra-subject and inter-subject brain decoding models. The brain responses identified by the decoding model reveal that a wide range of brain regions and functional interactions are recruited during semantics categorization. Especially, the working memory system exhibits significant contributions. Other substantially involved brain systems include emotion, attention, vision and language systems.

An optimized adaptive streaming framework for interactive immersive video experiences

This paper describes how optimized streaming strategies, based on MPEG-DASH, can be employed to power a new generation of interactive applications based on immersive video. The latter encompasses ultra-high-resolution, omni-directional and panoramic video. The goal is to deliver experiences that are made up of multiple videos of short duration, which can be joined at run-time in an order defined through user interactions. Applications of the technology are widespread, ranging from virtual walk through to interactive storytelling, the former of which will be featured in detail.

The main technological challenges tackled in this paper are to deliver these experiences in a seamless fashion, at the highest quality level allowed by network conditions and on a wide range of platforms, including the Web. Besides these, the paper focuses on the two-tier software architecture of the proposed framework, as well as a short evaluation to substantiate the validity of the proposed solutions.

Distortion minimize of streaming video in multiclient network

Streaming is a delivery of data from server to clients. The data is in form of packets in heterogeneous client environment packet would delay and lost. Multi clients finds its application in wide range of domains which includes 3 G cellular networks and ISM band connect to multi radio clients where clients get confidentiality of connecting with server. This includes detecting the connection of heterogeneous clients in the network. Packet delay happens while streaming of video in multi clients network aims to distort video which effects on quality. Analysis of packets delay or packet loss while streaming from server to client communicated between the nodes and works fine if every packets.

The proposed system targets to disclose the distortion of anonymous frames in a W-LAN network where Heuristic Algorithm is employed for packet loss and packet delay detection. The proposed work will find out the packet delay and packet loss of a frame for the analyzed video. The results can be obtained in windows form where each server windows associated with delivery and clients represents connection and packet delay or loss is reduced. The work completed up till now includes access network connection in static manner and analyzing video when it is completely deliver to client.