Cloning and aging in a VR family
Face cloning and animation considering wrinkle formation and aging are an aspiring goal and a challenging task. This paper describes a cloning method and an aging simulation in a family. We reconstruct a father, mother, son and daughter of one family and mix their shapes and textures in 3D to get virtual persons with some variation. The idea of reconstruction of a head is to detect features from two orthogonal pictures, modify a generic model with an animation structure and use an automatic texture mapping method. It is followed by a simple method to do 3D-shape interpolation and 2D morphing based on triangulation for experiments of mixing 3D heads between family members. Finally, wrinkles within facial animation and aging are generated based on detected feature points. Experiments are made to generate aging wrinkles on the faces of the son and the daughter.

title: MPEG-4 compatible faces from orthogonal photos
abstract: MPEG-4 is scheduled to become an international standard in March 1999. The paper demonstrates an experiment for a virtual cloning method and animation system, which is compatible with the MPEG-4 standard facial object specification. Our method uses orthogonal photos (front and side view) as input and reconstructs the 3D facial model. The method is based on extracting MPEG-4 face definition parameters (FDP) from photos, which initializes a custom face in a more capable interface, and deforming a generic model. Texture mapping is employed using an image composed of the two orthogonal images, which is done completely automatically. A reconstructed head can be animated immediately inside our animation system, which is adapted to the MPEG-4 standard specification of face animation parameters (FAP). The result is integrated into our virtual human director (VHD) system.

title: Real Face Communication in a Virtual World
abstract: This paper describes an efficient method to make an individual face for animation from several possible inputs and how to use this result for a realistic talking head communication in a virtual world. We present a method to reconstruct 3D facial model from two orthogonal pictures taken from front and side views. The method is based on extracting features from a face in a semiautomatic way and deforming a generic model. Texture mapping based on cylindrical projection is employed using a composed image from the two images. A reconstructed head is animated immediately and is able to talk with given text, which is transformed to corresponding phonemes and visemes. We also propose a system for individualized face-to-face communication through network using MPEG4.

title: Personalized face and speech communication over the Internet
abstract: We present our system for personalized face and speech communication over the Internet. The overall system consists of three parts: the cloning of real human faces to use as the representative avatars; the Networked Virtual Environment System performing the basic task of network and device management; and the speech system which includes a text-to-speech engine and a real time phoneme extraction engine from natural speech. The combination of these three elements provides a system to allow real humans, represented by their virtual counterparts, to communicate with each other even when they are geographically remote. In addition to this, all elements present use MPEG-4 as a common communication and animation standard and were designed and tested on the Windows operating system (OS). The paper presents the main aim of the work, the methodology and the resulting communication system.

title: Face recognition using computer-generated database
abstract: Many face database and recognition systems have been constructed in specially designed studios with various illuminations, poses, and expressions. However, none of these databases yet satisfies a large variation of poses and illuminations that permit the study of systematic 3D human face information, which results in an unsatisfactory success rate. It is caused primarily by the difficulty of data collection of facial images to satisfy the large variation of poses and illuminations to fully represent the 3D characteristics of human faces. We present how computer-generated database can be used for face recognition experiment focused on multiview face recognition/descriptor. We show multiview face data collection using rendering of 3D models. We also illustrate our approach how to build a face descriptor containing 3D information of human face using multiview concepts. This multiview face recognition descriptor is a 3D descriptor using the concept how much powerful a view influences over nearby views, so called as "quasiview " size

title: Mining Audit Data to Build Intrusion Detection Models
abstract: In this paper we discuss a data mining framework for constructing intrusion detection models. The key ideas are to mine system audit data for consistent and useful patterns of program and user behavior, and use the set of relevant system features presented in the patterns to compute (inductively learned) classifiers that can recognize anomalies and known intrusions. Our past experiments showed that classifiers can be used to detect intrusions, provided that sufficient audit data is available for training and the right set of system features are selected. We propose to use the association rules and frequent episodes computed from audit data as the basis for guiding the audit data gathering and feature selection processes. We modify these two basic algorithms to use axis attribute(s) as a form of item constraints to compute only the relevant ("useful") patterns, and an iterative level-wise approximate mining procedure to uncover the low frequency (but important) patterns. We report our experiments in using these algorithms on real-world audit data.

title: Toward Cost-Sensitive Modeling for Intrusion Detection and Response
abstract: Intrusion detection systems (IDSs) must maximize the realization of security goals while minimizing costs. In this paper, we study the problem of building cost-sensitive intrusion detection models. We examine the major cost factors associated with an IDS, which include development cost, operational cost, damage cost due to successful intrusions, and the cost of manual and automated response to intrusions. These cost factors can be qualified according to a defined attack taxonomy and site-specific security policies and priorities. We define cost models to formulate the total expected cost of an IDS, and present cost-sensitive machine learning techniques that can produce detection models that are optimized for user-defined cost metrics. Empirical experiments show that our cost-sensitive modeling and deployment techniques are effective in reducing the overall cost of intrusion detection.

title: RankCut - A Domain Independent Forward Pruning Method for Games
abstract: Forward pruning, also known as selective search, is now employed in many strong game-playing programs. In this paper, we introduce RankCut – a domain independent forward pruning technique which makes use of move ordering, and prunes once no better move is likely to be available. Since gameplaying programs already perform move ordering to improve the performance of αβ search, this information is available at no extra cost. As RankCut uses additional information untapped by current forward pruning techniques, RankCut is a complementary forward pruning method that can be used with existing methods, and is able to achieve improvements even when conventional pruning techniques are simultaneously employed. We implemented RankCut in a modern open-source chess program, CRAFTY. RankCut reduces the game-tree size by approximately 10%-40% for search depths 8-12 while retaining tactical reliability, when implemented alongside CRAFTY’s existing forward pruning techniques.

title: Anomaly detection using call stack information
abstract: The call stack of a program execution can be a very good information source for intrusion detection. There is no prior work on dynamically extracting information from the call stack and effectively using it to detect exploits. In this paper we propose a new method to do anomaly detection using call stack information. The basic idea is to extract return addresses from the call stack, and generate an abstract execution path between two program execution points. Experiments show that our method can detect some attacks that cannot be detected by other approaches, while its convergence and false positive performance is comparable to or better than the other approaches. We compare our method with other approaches by analyzing their underlying principles and thus achieve a better characterization of their performance, in particular on what and why attacks will be missed by the various approaches.

title: Spatial temporal concealment of lost blocks in coded video
abstract: When errors are introduced into a compressed video bit-stream, blocks of pixels are lost. The decoder attempts to conceal this loss to maximize the displayed picture quality. Previous approaches use either surrounding pixels in the current picture to conceal lost blocks (spatial concealment) or pixels from the previous picture (temporal concealment). We show how joint spatial temporal concealment can be implemented to provide higher quality concealment. To do that we model video sequences as mixtures of simple Markov processes and utilise the model for concealment of portions of video which are missing. This model allows us to combine spatial and temporal information in a seamless manner when performing concealment on the missing blocks.