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Section: Publications & Resources
Publication: IEEE Transactions on Image Processing
Visual attention is an important mechanism in the human visual system (HVS) and there have been numerous saliency detection algorithms designed for 2D images/video recently. However, the research for fixation detection of stereoscopic video is still limited and challenging due to the complicated depth and motion information.
Section: Publications & Resources
Publication: IEEE Transactions on Image Processing
In depth map coding, rate-distortion optimization for those pixels that will cause occlusion in view synthesis is a rather challenging task, since the synthesis distortion estimation is complicated by the warping competition and the occlusion order can be easily changed by the adopted optimization strategy.
Section: Publications & Resources
Publication: IEEE Transactions on Multimedia
This paper addresses the problem of encoding the video generated by the screen of an airplane cockpit. As other computer screens, cockpit screens consist of computer-generated graphics often atop a natural background. Existing screen content coding schemes fail notably in preserving the readability of textual information at the low bitrates required in avionic applications.
Section: Publications & Resources
Publication: IEEE Transactions on Multimedia
This paper presents a new method of secret three-dimensional object sharing (S3DOS), which allows sharing of three-dimensional (3-D) objects, while preserving its file format by selectively encrypting a 3-D object in order to sufficiently protect the visual nature of the content.
Section: Publications & Resources
Publication: IEEE Transactions on Multimedia
In past years, various encrypted algorithms have been proposed to fully or partially protect the multimedia content in view of practical applications. In the context of digital TV broadcasting, transparent encryption only protects partial content and fulfills both security and quality requirements.
Section: Publications & Resources
A key challenge in designing distributed particle filters is to minimize the communication overhead without compromising tracking performance. In this paper, we present two distributed particle filters that achieve robust performance with low communication overhead.
Section: Publications & Resources
Expander recovery is an iterative algorithm designed to recover sparse signals measured with binary matrices with linear complexity. In the paper, we study the expander recovery performance of the bipartite graph with girth greater than 4, which can be associated with a binary matrix with column correlations equal to either 0 or 1.
Section: Publications & Resources
We study the problem of distributed filtering for state space models over networks, which aims to collaboratively estimate the states by a network of nodes. Most of existing works on this problem assume that both process and measurement noises are Gaussian and their covariances are known in advance. In some cases, this assumption breaks down and no longer holds.
Section: Publications & Resources
Publication: IEEE Transactions on Signal Processing
This paper studies resilient distributed estimation under measurement attacks. A set of agents each makes successive local, linear, noisy measurements of an unknown vector field collected in a vector parameter. The local measurement models are heterogeneous across agents and may be locally unobservable for the unknown parameter.
Section: Publications & Resources
Publication: IEEE Transactions on Signal Processing
We consider the problem of decentralized consensus optimization, where the sum of n smooth and strongly convex functions are minimized over n distributed agents that form a connected network. In particular, we consider the case that the communicated local decision variables among nodes are quantized in order to alleviate the communication bottleneck in distributed optimization.
