709845
Supporting Live Video on Ad Hoc Wireless Networks: Unbalanced Multiple Description Coding, Single Path Transport and Recursive Error Concealment
Robust transmission of live video over ad hoc wireless networks presents new challenges: high bandwidth requirements are coupled with delay constraints; nodes are constrained in processing power and storage capacity; ad hoc wireless networks suffer from bursty packet losses that drastically degrade the viewing experience. Accordingly, we propose a simple, but practical unbalanced multiple description (UMD) codec that uses single path transport only. At the UMD decoder, the lost Low- Resolution (LR) frames can be receded from the corresponding ones of the correctly received High- Resolution (HR) stream. This makes LR more robust to packet losses and ensures continuous video playback. The simulation results show that the proposed UMD codec has higher decoded quality, smaller quality fluctuation and lower probability of pause than other error resilience techniques, especially when channel burstiness becomes large. We also propose a novel sequence-based error concealment (EC) algorithm for our UMD decoder. It recursively uses multi-frame recovery principle to frame-by-frame reduce error drift in the HR description with respect to the LR description. In fact, the algorithm can be applied to most UMD schemes. It has the advantage of working on integer-, half- or quarter- pixel precision and looking backward without buffering future frames. Experimental results show that error decreases the fastest if the UMD decoder uses our EC algorithm. It can provide satisfactory performance on both objective and subjective evaluation.
28434248
Optimized Rate Allocation for Unbalanced Multiple Description Video Coding Over Unreliable Packet Network
35782406
License management scheme with anonymous trust for digital rights management
One of the major issues raised by digital rights management systems concerns the protection of the user's privacy and anonymous consumption of content. However, most existing license management schemes for DRM systems do not support the protection of user privacy. Moreover, some other schemes such as PrecePt can only bind the license with a specified device though they concern privacy protection. In this paper, we propose a license management scheme named LMSAT (License Management Scheme with Anonymous Trust) which provides a more powerful and flexible license acquisition and usage tracking scheme to allow the user access the contents anytime, anywhere, and on any compliant devices anonymously.
44704902
Detection of Individual Microbubbles Using Wavelet Transform Based on a Theoretical Bubble Oscillation Model
Detecting individual microbubbles is important for the quantification of the amount of bubbles in the tissues, determination of microvascular volume and targeted microbubble imaging. We took the advantage of a theoretical bubble oscillation model to construct a matched wavelet, i.e. bubble wavelet as mother wavelet to detect individual microbubble using wavelet transform. The experimental echoes with different levels of added noises were processed. The results showed significant improvement even for an Echo-Noise-Ratio (ENRin) of -20 dB and the spatial location demonstrated very close agreement with the original experimental echo. This technique was much better than those based on harmonic analysis especially under the circumstance of short pulse insonation.
7375220
Dynamic User Modeling for Sketch-Based User Interface
This paper presents a strategy of dynamic user modeling for sketch-based user interface. A user model is defined as an incremental decision tree for a specific user. A drawing style modeling process is designed to model user's temporal drawing performances among inputting strokes, and to predict the possible shape in term of fuzzy matching. A user mediation process is proposed based on relevance feedback to capture users' drawing intentions and refine the recognition results. Experiments prove efficiency of the method.
9214943
A restart univariate estimation of distribution algorithm: sampling under mixed Gaussian and Lévy probability distribution
A univariate EDA denoted as ldquoLSEDA-glrdquo for large scale global optimization (LSGO) problems is proposed in this paper. Three efficient strategies: sampling under mixed Gaussian and Levy probability distribution, standard deviation control strategy and restart strategy are adopted to improve the performance of classical univariate EDA on LSGO problems. The motivation of such work is to extend EDAs to LSGO domain reasonably. Comparison among LSEDA-gl, EDA with standard deviation control strategy only (EDA-STDC) and similar EDA version ldquocontinuous univariate marginal distribution algorithmrdquo UMDAc is carried out on classical test functions. Based on the general comparison standard, the strengths and weaknesses of the algorithms are discussed. Besides, LSEDA-gl is tested on 7 functions with 100, 500, 1000 dimensions provided in the CECpsila2008 Special Session on LSGO. This work is also expected to provide a comparison result for the CECpsila2008 special session.
3197098
A Multi-Objective Hw-sw Co-Synthesis Algorithm Based on Quantum-Inspired Evolutionary Algorithm
Hardware–Software (HW–SW) co-synthesis is one of the key steps in modern embedded system design. Generally, HW–SW co-synthesis is to optimally allocate processors, assign tasks to processors, and schedule the processing of tasks to achieve a good balance among performance, cost, power consumption, etc. Hence, it is a typical multi-objective optimization problem. In this paper, a new multi-objective HW–SW co-synthesis algorithm based on the quantum-inspired evolutionary algorithm (MQEAC) is proposed. MQEAC utilizes multiple quantum probability amplitude vectors to model the promising areas of solution space. Meanwhile, this paper presents a new crossover operator to accelerate the convergence to the Pareto front and introduces a PE slot-filling strategy to improve the efficiency of scheduling. Experimental results show that the proposed algorithm can solve the typical multi-objective co-synthesis problems effectively and efficiently.
27086487
A Robust Iris Localization Algorithm via Radial Symmetry for Nonideal Capturing Condition
Iris localization is a key component of practical iris recognition system. Previous algorithms show good localization performances for iris images captured in the ideal conditions. However, in practice, the quality of iris image is greatly influenced by luminance, eyelashes, hair or glasses frame, which will cause mislocalization. In order to improve the robustness of iris localization, this paper proposes a new localization algorithm based on the radial symmetry transform, in which the radial symmetry characteristic of the pupil is utilized to realize iris localization. Experimental results show that the proposed algorithm can efficiently avoid the interference of luminance and other bad conditions, and realize robust precise localization in a real-time system.