16336933
Adaptive Video Watermarking Scheme
In this paper, a new adaptive watermarking scheme for uncompressed and compressed video is presented. The proposed method embeds the watermark in DC components by quantizing DC coefficients to reference values, instead of embedding the watermark in AC components. To increase robustness and perceptual invisibility, adaptive quantization control strategy (AQCS) and error compensation strategy (ECS) are introduced. Experimental results demonstrate the proposed watermarking scheme is robust and invisible, and is feasible for real time system implementation.
28754515
3D Object-based Scalable Wavelet Video Coding with Boundary Effect Suppression
This paper extends the lifting-based motion threading technique from the frame-based coding to the object-based coding, attracted by the unique advantages of the object-based coding that do not exist in other coding schemes. The boundary effects, which exist in spatial and temporal wavelet transforms due to the manner of object-based coding, are well suppressed by 3D shape adaptive discrete wavelet transform (3D SA-DWT) via the lifting implementation in a unified framework. Based on the proposed object-based motion threading technique, a 3D object-based scalable wavelet video coder is developed. Experimental results show that the proposed coder achieves good performance compared with the existing object-based coders, and provides the scalability functionality at the same time.
638941
Existence and Finiteness Conditions for Risk-Sensitive Planning: Results and Conjectures
Decision-theoretic planning with risk-sensitive planning objectives is important for building autonomous agents or decision-support systems for real-world applications. However, this line of research has been largely ignored in the artificial intelligence and operations research communities since planning with risk-sensitive planning objectives is more complicated than planning with risk-neutral planning objectives. To remedy this situation, we derive conditions that guarantee that the optimal expected utilities of the total plan-execution reward exist and are finite for fully observable Markov decision process models with non-linear utility functions. In case of Markov decision process models with both positive and negative rewards, most of our results hold for stationary policies only, but we conjecture that they can be generalized to non stationary policies.
1236601
Skewed symmetry groups
We introduce the term skewed symmetry groups and provide a complete theoretical treatment for 2D wallpaper groups under affine transformations. For the first time, a given periodic pattern can be classified not simply by its Euclidean symmetry group but,by its highest "potential" symmetry group under affine deformation. A concise wallpaper group migration map is constructed that separates the 17 affinely deformed wallpaper groups into small, distinct orbits. The practical value of this result includes a novel indexing and retrieval scheme for regular patterns, and a maximal-symmetry-based method for estimating shape and orientation from texture under unknown views.
12839905
Context sensitive vocabulary and its application in protein secondary structure prediction
Protein secondary structure prediction is an important step towards understanding the relation between protein sequence and structure. However, most current prediction methods use features difficult for biologists to interpret. In this paper, we present a new method that applies information retrieval techniques to solve the problem:we extract a context sensitive biological vocabulary for protein sequences and apply text classification methods to predict protein secondary structure. Experimental results show that our method performs comparably to the state-of-art methods. Furthermore, the context sensitive vocabularies can serve as a useful tool to discover meaningful regular expression patterns for protein structures.
753155
Spare Capacity Planning for Survivable Mesh Networks
The design of survivable mesh based STM networks has received considerable attention in recent years and is a complex multiconstraint optimization problem. In this paper, a new spare capacity planning methodology is proposed utilizing genetic algorithms. The method is based on forcing flows/traffic which are on paths that are disjoint to share backup spare capacity. The major advantages of the new approach are a polynomial time complexity and the capability of incorporating nonlinear variables such as nonlinear cost functions into the solution algorithm. Numerical results illustrating the form of the genetic algorithm solution and comparing the proposed methodology to existing techniques from the literature are presented.
15062986
Manifold-guaranteed out-of-core simplification of large meshes with controlled topological type
In this paper, a simple and efficient algorithm is proposed for manifold-guaranteed out-of-core simplification of large meshes with controlled topological type. By dual-sampling the input large mesh model, the proposed algorithm utilizes a set of Hermite data (sample points with normals) as an intermediate model representation, which allows the topological structure of the mesh model to be encoded implicitly and thus makes it particularly suitable for out-of-core mesh simplification. Benefiting from the construction of an in-core signed distance field, the proposed algorithm possesses a set of features including manifoldness of the simplified meshes, toleration of nonmanifold mesh data input, topological noise removal, topological type control and, sharp features and boundary preservation. A novel, detailed implementation of the proposed algorithm is presented, and experimental results demonstrate that very large meshes can be simplified quickly on a low-cost off-the-shelf PC with tightly bounded approximation errors and with time and space efficiency.