Balakrishnan Prabhakaran

A survey of quality of service in IEEE 802.11 networks

Developed as a simple and cost-effective wireless technology for best effort services, IEEE 802.11 has gained popularity at an unprecedented rate. However, due to the lack of built-in quality of service support, IEEE 802.11 experiences serious challenges in meeting the demands of multimedia services and applications. This article surveys 802.11 QoS schemes, including service differentiation in the MAC layer, admission control and bandwidth reservation in MAC and higher layers, and link adaptation in the physical layer, designed to meet these challenges by providing the necessary enhancements for the required QoS. Furthermore, the article addresses issues that arise when end-to-end QoS has to be guaranteed in todays pervasive heterogeneous wired-cum-wireless networks. Among these challenges, protocol interoperability, multihop scheduling, full mobility support, and seamless vertical handoff among multiple mobile/wireless interfaces are specifically addressed.

A Body Sensor Network With Electromyogram and Inertial Sensors: Multimodal Interpretation of Muscular Activities

The evaluation of the postural control system (PCS) has applications in rehabilitation, sports medicine, gait analysis, fall detection, and diagnosis of many diseases associated with a reduction in balance ability. Standing involves significant muscle use to maintain balance, making standing balance a good indicator of the health of the PCS. Inertial sensor systems have been used to quantify standing balance by assessing displacement of the center of mass, resulting in several standardized measures. Electromyogram (EMG) sensors directly measure the muscle control signals. Despite strong evidence of the potential of muscle activity for balance evaluation, less study has been done on extracting unique features from EMG data that express balance abnormalities. In this paper, we present machine learning and statistical techniques to extract parameters from EMG sensors placed on the tibialis anterior and gastrocnemius muscles, which show a strong correlation to the standard parameters extracted from accelerometer data. This novel interpretation of the neuromuscular system provides a unique method of assessing human balance based on EMG signals. In order to verify the effectiveness of the introduced features in measuring postural sway, we conduct several classification tests that operate on the EMG features and predict significance of different balance measures.

Synchronization models for multimedia presentation with user participation

This paper addresses the key issue of providingflexible multimedia presentation with user participation and suggests synchronization models that can specify the user participation during the presentation. We study models like the Petrinet-based hypertext model and the object composition Petri nets (OCPN). We suggest adynamic timed Petri nets structure that can model pre-emptions and modifications to the temporal characteristics of the net. This structure can be adopted by the OCPN to facilitate modeling of multimedia synchronization characteristics with dynamic user participation. We show that the suggested enhancements for the dynamic timed Petri nets satisfy all the properties of the Petri net theory. We use the suggested enhancements to model typical scenarios in a multimedia presentation with user inputs.

CHIMP: a framework for supporting distributed multimedia document authoring and presentation

A multimedia document consists of different media objects that are to be sequenced and presented according to temporal and spatial specifications. Collaborative authoring helps in simultaneous editing and viewing of a multimedia document by multiple authors. However, it may cause the objects composing a multimedia document to be distributed over a computer network. In this paper, we propose a framework for distributed multimedia document authoring and presentation. The salient features of this framework are: flexible temporal specification based on difference constraints, system and user defined access filters, local editing, format conversions of media objects, and flexible object retrieval schedules for handling variations in system parameters such as network throughput and buffer resources. We propose shortestpath based algorithms for solving difference constraints. We show how the proposed algorithms can handle local editing and access filtering of multimedia documents. We also describe how the difference constraints based temporal specifications can help in deriving a flexible object retrieval schedule.

Real-time classification of variable length multi-attribute motions

Multi-attribute motion data can be generated in many applications/ devices, such as motion capture devices and animations. It can have dozens of attributes, thousands of rows, and even similar motions can have different durations and different speeds at corresponding parts. There are no row-to-row correspondences between data matrices of two motions. To be classified and recognized, multi-attribute motion data of different lengths are reduced to feature vectors by using the properties of singular value decomposition (SVD) of motion data. The reduced feature vectors of similar motions are close to each other, while reduced feature vectors are different from each other if their motions are different. By applying support vector machines (SVM) to the feature vectors, we efficiently classify and recognize real-world multi-attribute motion data. With our data set of more than 300 motions with different lengths and variations, SVM outperforms classification by related similarity measures, in terms of accuracy and CPU time. The performance of our approach shows its feasibility of real-time applications to real-world data.

Segmentation and recognition of motion streams by similarity search

Fast and accurate recognition of motion data streams from gesture sensing and motion capture devices has many applications and is the focus of this article. Based on the analysis of the geometric structures revealed by singular value decompositions (SVD) of motion data, a similarity measure is proposed for simultaneously segmenting and recognizing motion streams. A direction identification approach is explored to further differentiate motions with similar data geometric structures. Experiments show that the proposed similarity measure can segment and recognize motion streams of variable lengths with high accuracy, without knowing beforehand the number of motions in a stream.

Retrieval schedules based on resource availability and flexible presentation specifications

Abstract. A distributed multimedia document presentation involves retrieval of objects from one or more document servers and their presentation at the client system. The presentation of the multimedia objects has to be carried out in accordance with the specification of temporal relationships between the objects. The retrieval of multimedia objects from the document server(s) is influenced by factors such as temporal specification of objects presentations, throughput offered by the network service provider, and the buffer resources on the client system. Flexibility in the temporal specification of the multimedia document may help in deriving an object retrieval schedule that can handle variations in network throughput and buffer resource availability. In this paper, we develop techniques for deriving a flexible object retrieval schedule for a distributed multimedia document presentation. The schedule is based on flexible temporal specification of the multimedia document using the difference constrai nts approach. We show how the derived retrieval schedule can be validated and modified to ensure that it can work with the offered network throughput and the available buffer resources.

Point-Based Manifold Harmonics

This paper proposes an algorithm to build a set of orthogonal Point-Based Manifold Harmonic Bases (PB-MHB) for spectral analysis over point-sampled manifold surfaces. To ensure that PB-MHB are orthogonal to each other, it is necessary to have symmetrizable discrete Laplace-Beltrami Operator (LBO) over the surfaces. Existing converging discrete LBO for point clouds, as proposed by Belkin et al. [CHECK END OF SENTENCE], is not guaranteed to be symmetrizable. We build a new point-wisely discrete LBO over the point-sampled surface that is guaranteed to be symmetrizable, and prove its convergence. By solving the eigen problem related to the new operator, we define a set of orthogonal bases over the point cloud. Experiments show that the new operator is converging better than other symmetrizable discrete Laplacian operators (such as graph Laplacian) defined on point-sampled surfaces, and can provide orthogonal bases for further spectral geometric analysis and processing tasks.

Middleware for streaming 3D progressive meshes over lossy networks

Streaming 3D graphics have been widely used in multimedia applications such as online gaming and virtual reality. However, a gap exists between the zero-loss-tolerance of the existing compression schemes and the lossy network transmissions. In this article, we propose a generic 3D middleware between the 3D application layer and the transport layer for the transmission of triangle-based progressively compressed 3D models. Significant features of the proposed middleware include. 1) handling 3D compressed data streams from multiple progressive compression techniques. 2) considering end user hardware capabilities for effectively saving the data size for network delivery. 3) a minimum cost dynamic reliable set selector to choose the transport protocol for each sublayer based on the real-time network traffic. Extensive simulations with TCP/UDP and SCTP show that the proposed 3D middleware can achieve the dual objectives of maintaining low transmission delay and small distortion, and thus supporting high quality 3D streaming with high flexibility.

Motion fault detection and isolation in Body Sensor Networks

Significant amount of research and development is being directed on monitoring activities of daily living of senior citizens who live alone as well as those affected with certain disorders such as Alzheimers and Parkinsons. A combination of sophisticated inertial sensing, wireless communication and signal processing technologies have made such a pervasive and remote monitoring possible. Due to the nature of the sensing and communication mechanisms, these monitoring sensors are susceptible to errors and failures. In this paper, we address the issue of identifying and isolating faulty sensors in a Body Sensor Network that is used for remote monitoring of daily living activities. We identify three different types of fault isolation strategies and propose both history-based and non-history based approaches.