10707976
Robust image authentication using content based compression
Abstract.Image authentication is becoming very important for certifying data integrity. A key issue in image authentication is the design of a compact signature that contains sufficient information to detect illegal tampering yet is robust under allowable manipulations. In this paper, we recognize that most permissible operations on images are global distortions like low-pass filtering and JPEG compression, whereas illegal data manipulations tend to be localized distortions. To exploit this observation, we propose an image authentication scheme where the signature is the result of an extremely low-bit-rate content-based compression. The content-based compression is guided by a space-variant weighting function whose values are higher in the more important and sensitive region. This spatially dependent weighting function determines a weighted norm that is particularly sensitive to the localized distortions induced by illegal tampering. It also gives a better compactness compared to the usual compression schemes that treat every spatial region as being equally important. In our implementation, the weighting function is a multifovea weighted function that resembles the biological foveated vision system. The foveae are salient points determined in the scale-space representation of the image. The desirable properties of multifovea weighted function in the wavelet domains fit nicely into our scheme. We have implemented our technique and tested its robustness and sensitivity for several manipulations.
7343489
Feature difference analysis in video authentication system
In most video authentication systems, the difference between features of the original and received videos is often used to decide the authenticity. In this paper, by employing mutual information to represent the similarity between the original and received video frames, we theoretically analyze the relationship between the feature difference and the video distortion. The relationship we derived is applied to estimate the maximum allowable feature difference in a video authentication system and to show how the feature difference varies with quantization step. Experimental results demonstrate that the derived relationship is reasonable and helpful for designing a robust video authentication system.
62135913
Kernel-based method for tracking objects with rotation and translation
This paper addresses the issue of tracking translation and rotation simultaneously. Starting with a kernel-based spatial-spectral model for object representation, we define an l/sub 2/-norm similarity measure between the target object and the observation, and derive a new formulation to the tracking of translational and rotational object. Based on the tracking formulation, an iterative procedure is proposed. We also develop an adaptive kernel model to cope with varying appearance. Experimental results are presented for both synthetic data and real-world traffic video.
14317741
Interactive 3D modeling using only one image
For virtual reality systems, modeling of 3D objects and scenes is important and challenging. In this paper, we present an image-based interactive 3D modeling framework consisting of three major modules: photogrammetric modeling, human interaction, and texture mapping. These three modules are not sequentially used and they are mixed in the whole modeling process. The major idea is to explore the use of images in interactive modeling systems to achieve the automation. In particular, the use of only one image is addressed. On one side, unlike the common fully interactive modeling framework, the users are not required to specify some low level details interactively which can be derived automatically from the image. On the other side, it still requires human interactions to do some high level tasks that the algorithms are difficult to perform automatically. We have implemented the framework and experimental results are good.
15320041
Feature extraction of volume data based on multi-scale representation
In this paper, we present a novel algorithm that can detect and extract salient points as features in 3-D volume datasets. This algorithm extracts not only the locations of feature points, but also finds out the scales at which the features are most significant. It applies the scale-space theory by adaptively processing the input volume in a few discrete scales. The features points, as well as their scales, detected can be used for subsequent processing, such as content-based volume data authentication and content-based volume rendering.We have implemented the algorithm and tested its effectiveness on several volume datasets. Some optimization has also been done on time-consuming intermediate steps to speed up the feature detection process.
18712320
Decomposing polygon meshes by means of critical points
Polygon mesh is among the most common data structures used for representing objects in computer graphics. Unfortunately, a polygon mesh does not capture high-level structures, unlike a hierarchical model. In general, high-level abstractions are useful for managing data in applications. In this paper, we present a method for decomposing an object represented in polygon meshes into components by means of critical points. The method consists of steps to define the root vertex of the object, define a function on the polygon meshes, compute the geodesic tree and critical points, decide the decomposition order, and extract components using backwards flooding. We have implemented the method. The preliminary results show that it works effectively and efficiently. The decomposition results can be useful for applications such as 3D model retrieval and morphing.
19558398
Gestures for Embodied Agents with Logic Programming
The paper discusses how distributed logic programming can be used to define and control the hand gestures of embodied agents in virtual worlds, by using the STEP language as an interface between the constructs of logic programming and the humanoid model defined in Virtual Reality Modelling Language (VRML). By using this framework, different gesture dictionaries can be defined and variants of a hand gesture, according to dynamically changing factors, can be generated on the fly. The approach is tested on the demanding demonstrator of conducting, providing experience, also on time performance of the animation.
12410756
Reasoning with Multi-version Ontologies: A Temporal Logic Approach
In this paper we propose a framework for reasoning with multi-version ontology, in which a temporal logic is developed to serve as its semantic foundation. We show that the temporal logic approach can provide a solid semantic foundation which can support various requirements on multi-version ontology reasoning. We have implemented the prototype of MORE (Multi-version Ontology REasoner), which is based on the proposed framework. We have tested MORE with several realistic ontologies. In this paper, we also discuss the implementation issues and report the experiments with MORE.
16942431
A graph model for E-commerce recommender systems
Information overload on the Web has created enormous challenges to customers selecting products for online purchases and to online businesses attempting to identify customers' preferences efficiently. Various recommender systems employing different data representations and recommendation methods are currently used to address these challenges. In this research, we developed a graph model that provides a generic data representation and can support different recommendation methods. To demonstrate its usefulness and flexibility, we developed three recommendation methods: direct retrieval, association mining, and high-degree association retrieval. We used a data set from an online bookstore as our research test-bed. Evaluation results showed that combining product content information and historical customer transaction information achieved more accurate predictions and relevant recommendations than using only collaborative information. However, comparisons among different methods showed that high-degree association retrieval did not perform significantly better than the association mining method or the direct retrieval method in our test-bed.
1948717
Reusable Gestures for Interactive Web Agents
In this paper we present an approach to define reusable gestures for embodied web agents, given according to the H-anim standard for VRML. We identify the dimensions to compare gestures and criteria to circumscribe a set of gestures an avatar should be endowed with. Based on these dimensions and criteria, we propose a uniform way to define a wide range of gestures that may be adapted to particular circumstances and personal style. We have implemented our gesture library in STEP, which is a scripting language for humanoids based on dynamic logic. We will discuss the example of conducting music, to explain our approach to the parameterized definition and control of gestures. We conclude by briefly discussing issues for future research.
18313204
A taxonomy of web agents
We propose a taxonomy of Web agents, which encompasses agents that provide a text-based interface to, for example, information retrieval services as well as avatar-embodied guides that help visitors to navigate in virtual environments. Our taxonomy must be regarded as an instrument to delineate targets for research and the realization of prototype applications that demonstrate the usefulness of agent-based intelligence on the Web. In addition, we deploy our agent-taxonomy to establish the implications particular target applications have with respect to software architecture and computational resources.