14856574
Error Resilient Video Coding Using Unequally Protected Key Pictures
This paper proposes the use of unequally protected key pictures to prevent temporal error propagation in error-prone video communications. The key picture may either be an intra-coded picture or a picture using a long-term motion compensation reference picture through reference picture selection. The inter-coded key picture uses previous key pictures as motion compensation reference. Key pictures are better protected than other pictures using forward error correction in either source or transport coding. Simulation results show significantly improved error resiliency performance of the proposed technique compared to conventional methods.
14888347
Error Resilient Mode Decision in Scalable Video Coding
Error resilient macroblock mode decision has been extensively investigated in the literature for single-layer video coding, for which error resilient mode decision is also called as intra refresh. In this paper, we present a loss-aware rate-distortion optimized macroblock mode decision algorithm for scalable video coding, wherein more macroblock coding modes than intra and inter are involved. Thanks to the good performance, the proposed method has been adopted into the joint scalable video model by the joint video team.
36989079
Sub-picture: ROI coding and unequal error protection
Region-of-interest coding and unequal error protection are two important tools in video communication systems to improve the received visual quality. One common property of the two techniques is that unequal coding or transmission is applied to improve the quality of the most important parts of images. The proposed sub-picture coding technique facilitates both region-of-interest coding and unequal error protection by partitioning images to regions of interest and separating the corresponding coded data units from each other. Simulation results show that the overall subjective quality is considerably improved compared to the conventional coding schemes.
7392070
System and Transport Interface of H.264/AVC Scalable Extension
The scalable extension of H.264/AVC, known as scalable video coding or SVC, has recently been the main focus of the Joint Video Team. The higher level syntax of SVC follows the design principles of H.264/AVC. This allows the work towards an optimized file format and RTF payload format to be conducted in parallel with the core SVC specification. This paper provides an overview of the system and transport interface design of SVC, including the SVC high-level syntax and functionalities, SVC file format, and SVC RTF payload format.
14708720
Coding of faded scene transitions
Coding of a scene transition is often a challenging problem, from the compression efficiency point of view, because motion compensation may not be a powerful enough method to represent changes between pictures in the transition. This paper proposes a overlay coding technique for coding faded scene transitions. As shown by extensive simulations, over 50% bit-rate savings in both cross-fades and through-black fades compared to earlier techniques can be achieved. Overlay coding suits situations where video is edited manually or automatically.
2496902
Improved Error Concealment Using Scene Information
Signaling of scene information in coded bitstreams was proposed by the authors and adopted into the emerging video coding standard H.264 (also known as MPEG-4 part 10 or AVC) as a supplemental enhancement information (SEI) message. This paper proposes some improved error concealment methods for intra coded pictures and scene transition pictures using the signaled scene information. Simulation results show that the proposed methods outperform conventional techniques significantly.
1235699
High resolution tracking of non-rigid 3D motion of densely sampled data using harmonic maps
We present a novel fully automatic method for high resolution, nonrigid dense 3D point tracking. High quality dense point clouds of nonrigid geometry moving at video speeds are acquired using a phase-shifting structured light ranging technique. To use such data for the temporal study of subtle motions such as those seen in facial expressions, an efficient nonrigid 3D motion tracking algorithm is needed to establish inter-frame correspondences. The novelty of this paper is the development of an algorithmic framework for 3D tracking that unifies tracking of intensity and geometric features, using harmonic maps with added feature correspondence constraints. While the previous uses of harmonic maps provided only global alignment, the proposed introduction of interior feature constraints guarantees that nonrigid deformations are accurately tracked as well. The harmonic map between two topological disks is a diffeomorphism with minimal stretching energy and bounded angle distortion. The map is stable, insensitive to resolution changes and is robust to noise. Due to the strong implicit and explicit smoothness constraints imposed by the algorithm and the high-resolution data, the resulting registration/deformation field is smooth, continuous and gives dense one-to-one inter-frame correspondences. Our method is validated through a series of experiments demonstrating its accuracy and efficiency.
17258193
Spatiotemporal video segmentation based on graphical models
This paper proposes a probabilistic framework for spatiotemporal segmentation of video sequences. Motion information, boundary information from intensity segmentation, and spatial connectivity of segmentation are unified in the video segmentation process by means of graphical models. A Bayesian network is presented to model interactions among the motion vector field, the intensity segmentation field, and the video segmentation field. The notion of the Markov random field is used to encourage the formation of continuous regions. Given consecutive frames, the conditional joint probability density of the three fields is maximized in an iterative way. To effectively utilize boundary information from the intensity segmentation, distance transformation is employed in local objective functions. Experimental results show that the method is robust and generates spatiotemporally coherent segmentation results. Moreover, the proposed video segmentation approach can be viewed as the compromise of previous motion based approaches and region merging approaches.
23798301
The cognitive process of comprehension
Comprehension is the action or capability of understanding. Comprehension is a higher cognitive process of the brain that searches relations between a given object or attribute and other objects, attributes, and relations in the long-term memory, and establishes a representational model for the object or attribute by connecting it to appropriate clusters of memory. It is recognized that although knowledge and information are powerful, before any information can be possessed and processed, it should be comprehended properly. This paper intends to model one of the cognitive life functions, comprehension, in cognitive informatics. The mechanism and process of comprehension are described based on the cognitive model of the brain developed by Wang. Then, real-time process algebra (RTPA) is used to formally describe the comprehension process.
5326806
Modeling for Optimal Probability Prediction
We present a general modeling method for optimal probability prediction over future observations, in which model dimensionality is determined as a natural by-product. This new method yields several estimators, and we establish theoretically that they are optimal (either overall or under stated restrictions) when the number of free parameters is infinite. As a case study, we investigate the problem of fitting logistic models in finite-sample situations. Simulation results on both artificial and practical datasets are supportive.
13993519
Interval efficiency assessment using data envelopment analysis
This paper studies how to conduct efficiency assessment using data envelopment analysis (DEA) in interval and/or fuzzy input-output environments. A new pair of interval DEA models is constructed on the basis of interval arithmetic, which differs from the existing DEA models handling interval data in that the former is a linear CCR model without the need of extra variable alternations and uses a fixed and unified production frontier (i.e. the same constraint set) to measure the efficiencies of decision-making units (DMUs) with interval input and output data, while the latter is usually a nonlinear optimization problem with the need of extra variable alternations or scale transformations and utilizes variable production frontiers (i.e. different constraint sets) to measure interval efficiencies. Ordinal preference information and fuzzy data are converted into interval data through the estimation of permissible intervals and @a-level sets, respectively, and are incorporated into the interval DEA models. The proposed interval DEA models are developed for measuring the lower and upper bounds of the best relative efficiency of each DMU with interval input and output data, which are different from the interval formed by the worst and the best relative efficiencies of each DMU. A minimax regret-based approach (MRA) is introduced to compare and rank the efficiency intervals of DMUs. Two numerical examples are provided to show the applications of the proposed interval DEA models and the preference ranking approach.