Javed I. Khan

Eye movement prediction by Kalman filter with integrated linear horizontal oculomotor plant mechanical model

The goal of this paper is to predict future horizontal eye movement trajectories within a specified time interval. To achieve this goal a linear horizontal oculomotor plant mechanical model is developed. The model consists of the eye globe and two extraocular muscles: lateral and medial recti. The model accounts for such anatomical properties of the eye as muscle location, elasticity, viscosity, eye-globe rotational inertia, muscle active state tension, length tension and force velocity relationships. The mathematical equations describing the oculomotor plant mechanical model are transformed into a Kalman filter form. Such transformation provides continuous eye movement prediction with a high degree of accuracy. The model was tested with 21 subjects and three multimedia files. Practical application of this model lies with direct eye gaze input and interactive displays systems as a method to compensate for detection, transmission and processing delays.

Predictive perceptual compression for real time video communication

Approximately 2 degrees in our 140 degree vision span has sharp vision. Many researchers have been fascinated by the idea of eye-tracking integrated perceptual compression of an image or video, yet any practical system has yet to emerge. The unique challenge presented by real time perceptual video streaming is how to handle the fast nature of the human eye and provide its integration with computationally intensive video transcoding scheme. The delay introduced by video transmission in the network presents a difficulty. This delay creates a problem when we try to use information about eye movements for perceptual encoding. In this paper we discuss a new approach to the eye-tracker based video compression. Rather than relying on the point of gaze, this novel scheme tracks a vicinity of interest and offers a prediction mechanism for eye movements. The described system compensates the interim eye movements between the sampling and actual coding. The proposed scheme can be applied to a large variety of todays video compression standards. We have developed an eye gaze-aware MPEG-2 transcoder that can perceptually re-encode a live video stream in real time. The experiments we have conducted illustrate the substantial impact this integrated prediction method has on perceptual video compression and bit-rate reduction.

Kalman filtering in the design of eye-gaze-guided computer interfaces

In this paper, we design an Attention Focus Kalman Filter (AFKF) - a framework that offers interaction capabilities by constructing an eye-movement language, provides real-time perceptual compression through Human Visual System (HVS) modeling, and improves systems reliability. These goals are achieved by an AFKF through identification of basic eye-movement types in real-time, the prediction of a users perceptual attention focus, and the use of the eyes visual sensitivity function and eye-position data signal de-noising.

Characteristics of multidimensional holographic associative memory in retrieval with dynamically localizable attention

This paper presents the performance analysis (capacity and retrieval accuracy) of multidimensional holographic associative memory (MHAC). MHAC has the unique ability to retrieve pattern-associations with changeable attention. In attention actuated retrieval the user can dynamically select any subset of the elements in the example query pattern and expect the memory to confine its associative match only within the specified field of attention. Existing artificial associative memories lack this ability. Also most of these models need at least 50% of bits in the input pattern to be correct for successful retrieval. MHAC, with the unique ability of localizable attention, can retrieve information correctly even with cues as small as 10% of the query frame. This paper investigates the performance of MHAC in attention actuated retrieval both analytically and experimentally. Besides confirmation, the experiments also identify an operational range space (ORS) for this memory within which various attention based applications can be built with a performance guarantee.

Motion based object tracking in MPEG-2 stream for perceptual region discriminating rate transcoding

Object based bit allocation can result in significant improvement in the perceptual quality of relatively low bit-rate video. In this paper we describe a novel content aware video transcoding technique that can accept high-level description of video objects and extract them from incoming video stream and use it for perceptual encoding based extreme video downscaling.

Computing in social networks with relationship algebra

Communities are the latest phenomena on the Internet. At the heart of each community lies a social network. In this paper, we show a generalized framework to understand and reason in social networks. Previously, researchers have attempted to use inference-specific type of relationships. We propose a framework to represent and reason with general case of social relationship network in a formal way. We call it relationship algebra. In the paper, we first present this algebra then show how this algebra can be used for various interesting computing on a social network weaved in the virtual communities. We show applications such as determining reviewers in a semi-professional network maintained by conference management systems, finding conflict of interest in a publication system, or to infer various trust relationships in a community of close associates, etc. We also show how future community networks can be used to determine who should be immunized in the case of a contagious disease outbreak and how these networks could be used in crime prevention, etc.

Prefetch scheduling for composite hypermedia

Composite hypermedia documents are fast becoming ubiquitous in the Web. More Websites are effectively serving hypermedia however with hypertext technology. We explore a novel segment-based background prefetch technique that utilizes the rendering properties of various individual media elements and their interdependencies. The technique can accelerate surfing in composite hypermedia.

Relationship Algebra for Computing in Social Networks and Social Network Based Applications

Online communities are the latest phenomena on the Internet. At the heart of each community lies a social network. In this paper, we show a generalized framework to understand and reason in social networks. Previously, researchers have attempted to use inference-specific type of relationships. In this paper, we propose a framework to represent and reason with general case of social relationship network in a formal way. We call it relationship algebra. This paper presents this algebra and then shows how this algebra can be used for various interesting computations on a social network weaved in the virtual communities

Exploiting Webspace organization for accelerating Web prefetching

We explore how the structure of Webspace can be used for accelerated Web prefetch. We have conducted experiments based on a novel hyperspace aware prefetch proxy and have studied the prefetch performance on several dominant hyperspace patterns. We assess the systems responsiveness and background loads for various user interaction duration, surfing and prefetch sequences. The results show that Webspace awareness can help in improving prefetch performance. We also provide an interesting insight toward a framework where the professional content developers can gain more control towards authoring prefetch friendly collection for increased site responsiveness.

A Study of Problem Difficulty Evaluation for Semantic Network Ontology Based Intelligent Courseware Sharing

Testing and evaluation is an integral part of the learning process. Educators have often tried to device methods for design of test-ware. Intelligent design and compilation of test-ware is a very interesting problem with immense applications. This research aims at automating the process of intelligent design of test-ware by providing qualitative assessment of questions. In this attempt, we provide some synthetic parameters for the evaluation of question in its concept space. The parameters are tested in some real world scenarios and intuitive inferences are deduced predicting the performance of the parameters. It is observed that the difficulty of a question is often a function of the concepts it tests. Concept knowledge can be represented in the form of linked concepts in semantic nets, the links representing the relationships between the concepts. If this directed graph is known, complexity of a question can be computed by synthetic means.