Data-based dynamic haptic interaction model with deformable 3D objects

The data-based modeling of the haptic interaction simulation is a growing trend in research. These techniques offer a quick alternative to parametric modeling of the simulation. So far, most of the use of the data-based techniques was applied to static simulations. This paper introduces how to use data-based model in dynamic simulations. This ensures realistic behavior and produce results that are very close to parametric modeling. The results show that a quick and accurate response can be achieved using the proposed methods.

Design of a compact microfludic device for controllable cell distribution

A compact microfluidic device with 96 microchambers allocated within four circular units was designed and examined for cell distribution. In each unit, cells were distributed to the surrounding chambers radially from the center. The circular arrangement of the chambers makes the design simple and compact. A controllable and quantitative cell distribution is achievable in this device. This design is significant to the microfluidic applications where controllable distribution of cells in multipule microchambers is demanded.

Data-driven computation of contact dynamics during two-point manipulation of deformable objects

This study represents a preliminary step towards data-driven computation of contact dynamics during manipulation of deformable objects at two points of contact. A modeling approach is proposed that characterizes the individual interaction at both points and the mutual effects of the two interactions on each other via a set of parameters. Both global as well as local coordinate systems are tested for encoding the contact mechanics. Artificial neural networks are trained on simulated data to capture the object behavior. A comparison of test data with the output of the trained system reveals a mean squared error percentage between 1% and 3% for simple interactions.

Grasping virtual objects with multi-point haptics

The majority of commercially available haptic devices offer a single point of haptic interaction. These devices are limited when it is desirable to grasp with multiple fingers in applications including virtual training, telesurgery and telemanipulation. Multipoint haptic devices serve to facilitate a greater range of interactions. This paper presents a gripper attachment to enable multi-point haptic grasping in virtual environments. The approach employs two Phantom Omni haptic devices to independently render forces to the user's thumb and other fingers. Compared with more complex approaches to multi-point haptics, this approach provides a number of advantages including low-cost, reliability and ease of programming. The ability of the integrated multi-point haptic platform to interact within a CHAI 3D virtual environment is also presented.

A multi-point haptic platform for grasping and manipulating virtual objects

This work presents a multi-point haptic platform that employs two Phantom Omni haptic devices. A gripper attachment connects to both devices and enables multi-point haptic grasping in virtual environments. In contrast to more complex approaches, this setup benefits from low-cost, reliability, and ease of programming while being capable of independently rendering forces to each of the user’s fingertips. The ability to grasp with multiple points potentially lends itself to applications such as virtual training, telesurgery and telemanipulation.

A cooperative cache architecture in support of caching multimedia objects in MANETs

This paper presents a cooperative caching architecture suitable for continuous media (CM) proxy caching in MANET environments. The proposed scheme introduces an application manager component, which is interposed between traditional Internet CM applications and the network layer. The application manager transparently performs data location and service migration of active CM streaming sessions so as to exploit nearby data sources based on the dynamic topology of a MANET. We propose two data location schemes - Cache-State - a link-state based scheme and Reactive - an on-demand scheme. Since service migration can occur frequently, the application manager uses soft-state signaling techniques to communicate between remote application managers by translating hard-state application signaling, such as Real Time Streaming Protocol (RTSP) into soft-state messages. The proposed schemes are evaluated through simulation studies using the NS simulator. Simulation studies show that both Cache-State and Reactive schemes demonstrate significant QoS improvements and reduced bandwidth consumption.

A flexible receiver-driven cache replacement scheme for continuous media objects in best-effort networks

In this paper, we investigate the potential of caching to improve quality of reception (QoR) in the context of continuous media applications over best-effort networks. Specifically, we investigate the influence of parameters such as loss rate, jitter, delay and area in determining a proxy's cache contents. We propose the use of a flexible cost function in caching algorithms and develop a framework for benchmarking continuous media caching algorithms. The cost function incorporates parameters in which, an administrator and or a client can tune to influence a proxy's cache. Traditional caching systems typically base decisions around static schemes that do not take into account the interest of their receiver pool. Based on the flexible cost function, an improvised Greedy Dual (GD) algorithm called GD-multi has been developed for layered multiresolution multimedia streams. The effectiveness of the proposed scheme is evaluated by simulation-based performance studies. Performance of several caching schemes are evaluated and compared with those of the proposed scheme. Our empirical results indicate GD-multi performs well despite employing a generalized caching policy.

On the incremental learning and recognition of the pattern of movement of multiple labelled objects in dynamic scenes

In this paper we discuss combining incremental learning and incremental recognition to classify patterns consisting of multiple objects, each represented by multiple spatio-temporal features. Importantly the technique allows for ambiguity in terms of the positions of the start and finish of the pattern. This involves a progressive classification which considers the data at each time instance in the query and thus provides a probable answer before all the query information becomes available. We present two methods that combine incremental learning and incremental recognition: a time instance method and an overall best match method.

On the automated interpretation and indexing of American football

This work combines natural language understanding and image processing with incremental learning to develop a system that can automatically interpret and index American Football. We have developed a model for representing spatio-temporal characteristics of multiple objects in dynamic scenes in this domain. Our representation combines expert knowledge, domain knowledge, spatial knowledge and temporal knowledge. We also present an incremental learning algorithm to improve the knowledge base as well as to keep previously developed concepts consistent with new data. The advantages of the incremental learning algorithm are that is that it does not split concepts and it generates a compact conceptual hierarchy which does not store instances.

Two-dimensional string notation for representing video sequences

Most current work on video indexing concentrates on queries which operate over high level semantic information which must be entirely composed and entered manually. We propose an indexing system which is based on spatial information about key objects in a scene. These key objects may be detected automatically, with manual supervision, and tracked through a sequence using one of a number of recently developed techniques. This representation is highly compact and allows rapid resolution of queries specified by iconic example. A number of systems have been produced which use 2D string notations to index digital image libraries. Just as 2D strings provide a compact and tractable indexing notation for digital pictures, a sequence of 2D strings might provide an index for a video or image sequence. To improve further upon this we reduce the representation to the 2D string pair representing the initial frame, and a sequence of edits to these strings. This takes advantage of the continuity between frames to further reduce the size of the notation. By representing video sequences using string edits, a notation has been developed which is compact, and allows querying on the spatial relationships of objects to be performed without rebuilding the majority of the scene. Calculating ranks of objects directly from the edit sequence allows matching with minimal calculation, thus greatly reducing search time. This paper presents the edit sequence notation and algorithms for evaluating queries over image sequences. A number of optimizations which represent a considerably saving in search time is demonstrated in the paper.

Observation-switching linear dynamic systems for tracking humans through unexpected partial occlusions by scene objects

This paper focuses on the problem of tracking people through occlusions by scene objects. Rather than relying on models of the scene to predict when occlusions will occur as other researchers have done, this paper proposes a linear dynamic system that switches between two alternatives of the position measurement in order to handle occlusions as they occur. The filter automatically switches between a foot-based measure of position (assuming z = Q) to a head-based position measure (given the person's height) when an occlusion of the person's lower body occurs. No knowledge of the scene or its occluding objects is used. Unlike similar research [2, 14], the approach does not assume a fixed height for people and so is able to track humans through occlusions even when they change height during the occlusion. The approach is evaluated on three furnished scenes containing tables, chairs, desks and partitions. Occlusions range from occlusions of legs, occlusions whilst being seated and near-total occlusions where only the person's head is visible. Results show that the approach provides a significant reduction in false-positive tracks in a multi-camera environment, and more than halves the number of lost tracks in single monocular camera views.