Multimodal Tracking Research Articles

Minimal Invasive Urologic Surgery and Postoperative Ileus

Postoperative ileus (POI) is the most common cause of prolonged length of hospital stays (LOS) and associated healthcare costs. The advent of minimal invasive technique was a major breakthrough in the urologic landscape with great potential to progress in the future. In the field of gastrointestinal surgery, several studies had reported lower incidence rates for POI following minimal invasive surgery compared to conventional open procedures. In contrast, little is known about the effect of minimal invasive approach on the recovery of bowel motility after urologic surgery. We performed an overview of the potential benefit of minimal invasive approach on POI for urologic procedures. The mechanisms and risk factors responsible for the onset of POI are discussed with emphasis on the advantages of minimal invasive approach. In the urologic field, POI is the main complication following radical cystectomy but it is rarely of clinical significance for other minimal invasive interventions. Laparoscopy or robotic assisted laparoscopic techniques when studied individually may reduce to their own the duration and prevent the onset of POI in a subset of procedures. The potential influence of age and urinary diversion type on postoperative ileus is contradictory in the literature. There is some evidence suggesting that BMI, blood loss, urinary extravasation, existence of a major complication, bowel resection, operative time and transperitoneal approach are independent risk factors for POI. Treatment of POI remains elusive. One of the most important and effective management strategies for patients undergoing radical cystectomy has been the development and use of enhanced recovery programs. An optimal rational strategy to shorten the duration of POI should incorporate minimal invasive approach when appropriate into multimodal fast track programs designed to reduce POI and shorten LOS.

Left atrial structure and functional quantitation using cardiac magnetic resonance: comparison of manual delineation vs. multimodality tissue tracking based semi-automated methods

Background Left atrium (LA) volume and function are important markers of cardiovascular disease. LA volume can be assessed by several different methods. In clinical practice, the Simpson’s method is well accepted as a reference standard, although there is no standardization for LA volume calculations. We aimed to compare the estimations of LA volume by the Simpson’s method and the modified biplane Simpson’s method; and to introduce Multimodality Tissue Tracking (MTT, Japan, Toshiba) as a new semi-automated method for quantifying LA function based on tissue feature tracking. Methods Thirty subjects (mean age: 71.3 ± 8.7, 87% male) including twenty subjects with cardiovascular events (4 atrial fibrillation, 18 myocardial scar from late gadolinium enhancement, 2 heart failure) and ten healthy subjects, with CMR imaging were evaluated in the Multi-Ethnic Study of Atherosclerosis (MESA). LA volumes were measured using the modified biplane Simpson’ sm ethod from 2- and 4-chamber projections and the original Simpson’s method using short-axis slices. For the manual methods, LA endo- and epicardial boundaries were delineated at left-ventricular end-diastole (Vmin), end-systole (Vmax) and just before the pre-atrial contraction (VpreA). Using MTT, LA endocardial and epicardial borders were manually delineated at end-systole and the boundaries were propagated automatically throughout the cardiac

Hybrid tracking system for robust fiducials registration in augmented reality

An effective augmented reality system requires an accurate registration of virtual graphics on real images. In this work, we developed a multi-modal tracking architecture for object identification and occlusion handling. Our approach combines several sensors and techniques to overcome the environment changes. This architecture is composed of a first coded targets registration module based on a hybrid algorithm of pose estimation. To manage partial target occlusions, a second module based on a robust method for feature points tracking is developed. The latest component of the system is the hybrid tracking module. This multi-sensors part handles total target occlusions issue. Experiments with the multi-modal system proved the effectiveness of the proposed tracking approach and occlusion handling in augmented reality applications.

Predictors of Successful Tracking over Time in a Homeless Population

Optimal understanding of the longitudinal course of homelessness requires research methodologies for successful tracking of this difficult-to-follow population (McKenzie et al., 1999). It is important to enroll and retain participants in research populations to be able to generalize findings to the populations they represent. Challenges of tracking marginalized populations over time are well recognized (Bindman, Grumbach, Keane, & Lurie, 1993; Conover et al., 1997; Kleschinsky, Bosworth, Nelson, Walsh, & Shaffer, 2009; Pollio, Thompson, & North, 2000), and tracking is complicated by substance use, psychiatric illness, and socioeconomic deprivation that are inherent in this population (North, Eyrich, Pollio, & Spitznagel, 2004). A recent review by McKenzie, Tulsky, Long, Chesney, and Moss (1999) described 10 strategies for successful tracking of marginalized populations, emphasizing multimodal tracking methods and team organization and training. Three noteworthy studies have obtained successful tracking rates of 75% over 12 months (Wright, Allen, & Devine, 1995), 82% over 24 months (Hough, Tarke, Renker, Shields, & Glatstein, 1996), and 83% over 12 months (Cohen et al., 1993). Conover's group (Conover et al., 1997), following an ethnographic approach, achieved virtually complete follow-up of homeless mentally ill men over 18 months, but this effort was part of a long-term intervention project designed for continuous participant engagement.

Online adaptive feature weighting for spatiogram-bank tracking

In this paper, we introduce a new adaptive feature weighting framework for multi-modal tracking. Our proposed tracker can compactly and efficiently handle multiple sources of tracking data, such as colour, brightness, gradient orientation and thermal infrared, and adaptively weight the sources based on their reliability for tracking. The adaptive weight selection mechanism is inspired by the state-of-the-art Collins tracker, but instead of treating the tracked object as a bag of features, it takes advantage of the spatial information using a global object model. Additionally, our tracker incorporates scale into the weight selection process and is shown to outperform the Collins tracker in an extensive video evaluation.

Synthesis and bio-functionalization of magnetic nanoparticles for medical diagnosis and treatment

The synthesis of multifunctional magnetic nanoparticles (NPs) is a highly active area of current research located at the interface between materials science, biotechnology and medicine. By virtue of their unique physical properties magnetic nanoparticles are emerging as a new class of diagnostic probes for multimodal tracking and as contrast agents for MRI. Furthermore, they show great potential as carriers for targeted drug and gene delivery, since reactive agents, such as drug molecules or large biomolecules (including genes and antibodies), can easily be attached to their surface. On the other hand, the fate of the nanoparticles inside the body is mainly determined by the interactions with its local environment. These interactions strongly depend upon the size of the magnetic NPs but also on the individual surface characteristics, like charge, morphology and surface chemistry. This review not only summarizes the most common synthetic approaches for the generation of magnetic NPs, it also focuses on different surface modification strategies that are used today to enhance the biocompatibility of these NPs. Finally, key considerations for the application of magnetic NPs in biomedicine, as well as various examples for the utilization in multimodal imaging and targeted gene delivery are presented.

Design and realization of tracking feed antenna system

This paper describes the design and realization of a multi-mode tracking feed antenna system, for a circularly polarized wave, which can generate sum and difference patterns suitable for monopulse tracking in remote sensing earth stations. It uses TE11 and TE21 modes, in a smooth circular waveguide, to obtain the sum and difference patterns. The higher order mode, TE21 generated within the feed is separated from the fundamental mode, TE11 by using a mode coupler. Circular polarization is converted to linear polarization by pin polarizer septum. The design of the multimode corrugated horn and polarizer are described in some details. The prototyped horn designed here operates in the frequency range of 7.2-8.8GHz. Sum and delta patterns and polarizer axial ratio are presented. The close agreement between measured and simulated data validates the present design.

클러터 환경에서 다중센서 정보융합을 통한 유도성능 개선 연구

A MTG (Multimode Tracking and Guidance) system is employed to compensate for the limitations of individual seekers such as RF (Radio frequency) or IIR (Imaging Infra-red) and to improve the overall tracking and guidance performance in jamming, clutter, and adverse weather environments. In the MTG system, tracking filter, data association, and data fusion methods are important elements to maximize the effectiveness of precision homing missile guidance. This paper proposes the formulation of a Kalman filter for the estimation of line-of-sight rate from seeker measurements in missiles guided by proportional navigation. Also, we suggest the HPDA (Highest Probability Data Association) and data fusion methods of the MTG system for target tracking in the adverse environments. Mont-Carlo simulation is employed to evaluate the overall tracking performance and guidance accuracy.

Statistical Estimation and Adaptation for Visual Compensation in Object Tracking

The multi-modal tracking model in [ 1 ] enables the on-the-fly error compensation with low complexity by adopting acoustic sensors for the main tracking task and visual sensors for correcting possible tracking errors. The visual compensation process in the model is indispensable to the accurate tracking task in a dynamic object movement. This article proposes an algorithm to approximate the successful visual compensation rate appearing in the multi-modal tracking system. The acoustic sampling interval of the object signal and the random occurrence of transmission delays of multi-modal data are critical to the compensation process. Therefore, by using the two key factors as parameters, the algorithm called SEA can estimate the successful visual compensation of a tracking system. After we build up a tracking system, it is required to maintain the system at a certain level of tracking accuracy. This task can be done by controlling the aforementioned parameters since the visual compensation influences the tracking accuracy. Thus, we propose another algorithm called SEA2 for the parameter adaptation. The algorithm controls only acoustic sampling interval due to the easiness of adjustment and having the main impact on the success of the visual compensation. From the algorithm validation, we show the SEA properly quantifies the visual compensation process successfully occurring in the tracking scenarios, and SEA2 is feasible for parameter adaptation and achieving the target level of accuracy.

On Addressing Network Synchronization in Object Tracking with Multi-modal Sensors

The performance of a tracking system is greatly increased if multiple types of sensors are combined to achieve the objective of the tracking instead of relying on single type of sensor. To conduct the multi-modal tracking, we have previously developed a multi-modal sensor-based tracking model where acoustic sensors mainly track the objects and visual sensors compensate the tracking errors [1]. In this paper, we find a network synchronization problem appearing in the developed tracking system. The problem is caused by the different location and traffic characteristics of multi-modal sensors and non-synchronized arrival of the captured sensor data at a processing server. To effectively deliver the sensor data, we propose a time-based packet aggregation algorithm where the acoustic sensor data are aggregated based on the sampling time and sent to the server. The delivered acoustic sensor data is then compensated by visual images to correct the tracking errors and such a compensation process improves the tracking accuracy in ideal case. However, in real situations, the tracking improvement from visual compensation can be severely degraded due to the aforementioned network synchronization problem, the impact of which is analyzed by simulations in this paper. To resolve the network synchronization problem, we differentiate the service level of sensor traffic based on Weight Round Robin (WRR) scheduling at the routers. The weighting factor allocated to each queue is calculated by a proposed Delay-based Weight Allocation (DWA) algorithm. From the simulations, we show the traffic differentiation model can mitigate the non-synchronization of sensor data. Finally, we analyze expected traffic behaviors of the tracking system in terms of acoustic sampling interval and visual image size.

Multimodal augmented reality tangible gaming

This paper presents tangible augmented reality gaming environment that can be used to enhance entertainment using a multimodal tracking interface. Players can interact using different combinations between a pinch glove, a Wiimote, a six-degrees-of-freedom tracker, through tangible ways as well as through I/O controls. Two tabletop augmented reality games have been designed and implemented including a racing game and a pile game. The goal of the augmented reality racing game is to start the car and move around the track without colliding with either the wall or the objects that exist in the gaming arena. Initial evaluation results showed that multimodal-based interaction games can be beneficial in gaming. Based on these results, an augmented reality pile game was implemented with goal of completing a circuit of pipes (from a starting point to an end point on a grid). Initial evaluation showed that tangible interaction is preferred to keyboard interaction and that tangible games are much more enjoyable.

A dynamic and extensible workflow-oriented software framework for image-guided therapy

Objective The software requirements for computer-aided navigation tools in image-guided therapy become increasingly complex as a result of new imaging and tracking hardware, novel application areas and regulatory restrictions. The objective of this work was to develop a new software framework to meet the needs of emerging image-guided procedures and therapies that require multi-modal imaging and tracking.

Multi-modal tracking of people using laser scanners and video camera

Inspite extensive research on visual tracking of multiple people in computer vision area, the robustness and usability of visual trackers are still discouraging. Recently, a few laser-based detection and tracking methods have been developed in robotics area. However, poor features provided by laser data make the tracker fail in many situations. In this paper, we present a novel method that aims at reliably detecting and tracking multiple people in an open area. Multiple laser scanners and one camera are used as input sensors. In detection stage, laser-based detection algorithm captures newly appeared people and initializes the mean-shift-based visual tracker. In tracking stage, laser-based feet trajectory tracking result and visual body region tracking result are combined with a decision-level Bayesian fusion method. The experimental results demonstrate reliable and real-time performance of the method.

Thermo-visual feature fusion for object tracking using multiple spatiogram trackers

In this paper, we propose a framework that can efficiently combine features for robust tracking based on fusing the outputs of multiple spatiogram trackers. This is achieved without the exponential increase in storage and processing that other multimodal tracking approaches suffer from. The framework allows the features to be split arbitrarily between the trackers, as well as providing the flexibility to add, remove or dynamically weight features. We derive a mean-shift type algorithm for the framework that allows efficient object tracking with very low computational overhead. We especially target the fusion of thermal infrared and visible spectrum features as the most useful features for automated surveillance applications. Results are shown on multimodal video sequences clearly illustrating the benefits of combining multiple features using our framework.

Robust multimodal audio–visual processing for advanced context awareness in smart spaces

Identifying people and tracking their locations is a key prerequisite to achieving context awareness in smart spaces. Moreover, in realistic context-aware applications, these tasks have to be carried out in a non-obtrusive fashion. In this paper we present a set of robust person-identification and tracking algorithms, based on audio and visual processing. A main characteristic of these algorithms is that they operate on far-field and un-constrained audio---visual streams, which ensure that they are non-intrusive. We also illustrate that the combination of their outputs can lead to composite multimodal tracking components, which are suitable for supporting a broad range of context-aware services. In combining audio---visual processing results, we exploit a context-modeling approach based on a graph of situations. Accordingly, we discuss the implementation of realistic prototype applications that make use of the full range of audio, visual and multimodal algorithms.

A Monocular Pointing Pose Estimator for Gestural Instruction of a Mobile Robot

We present an important aspect of our human-robot communication interface which is being developed in the context of our long-term research framework PERSES dealing with highly interactive mobile companion robots. Based on a multi-modal people detection and tracking system, we present a hierarchical neural architecture that estimates a target point at the floor indicated by a pointing pose, thus enabling a user to navigate a mobile robot to a specific target position in his local surroundings by means of pointing. In this context, we were especially interested in determining whether it is possible to accomplish such a target point estimator using only monocular images of low-cost cameras. The estimator has been implemented and experimentally investigated on our mobile robotic assistant HOROS. Although only monocular image data of relatively poor quality were utilized, the estimator accomplishes a good estimation performance, achieving an accuracy better than that of a human viewer on the same data. The achieved recognition results demonstrate that it is in fact possible to realize a user-independent pointing direction estimation using monocular images only, but further efforts are necessary to improve the robustness of this approach for everyday application.

The SIGN: A dynamic and extensible software framework for Image-Guided Therapy

The software requirements for computer-aided navigation tools in image-guided therapy are becoming increasingly complex as a result of new possibilities in imaging and tracking hardware, novel application areas and regulatory restrictions. A new software framework has been developed to meet the needs of emerging image-guided procedures and therapies that require multi-modal imaging and tracking. This framework accommodates dynamic data-structures, dynamic input and output interfaces for interventional devices, and dynamic visualization of data. Arbitrary, yet meaningful, connections can be established between these entities in order to implement customized applications that target specific clinical procedures. A series of demonstration applications have been developed in order to emphasize different aspects of the framework, and are presented here.

Cross-modal visual and vibrotactile tracking

The present study investigates tracking performance with tactile and/or visual presentation of target and cursor. The tactile display consisted of vibrators in a horizontal linear array on the torso, the visual display consisted of dots projected on a horizontal plane surrounding the observer. Both displays presented qualitatively identical information: direction in a horizontal plane. Participants performed two different tracking tasks with target and cursor presented to the same modality (either visual or tactile) or to different modalities (a visual target and a tactile cursor or vice versa). The errors in both cross-modal settings were well predicted by the uni-modal errors. This indicates that no additional costs are involved in cross-modal visual–vibrotactile tracking. Closer inspection of the data reveals that the tactile modality is less suited for processing external disturbances. These results give directions on how to allocate information to the visual and tactile modalities in a multi-modal tracking interface, such as those applied in military cockpits.

Brief but Comprehensive Psychotherapy: The Multimodal Way

Who Is the Briefest of Them All? Brief but Comprehensive Psychotherapy: The Multimodal Way Arnold A. Lazarus. New York: Springer Publishing Company, 1997, 177 pp., $35.95 (hardcover) In Brief but Comprehensive Psychotherapy: The Multimodal Way, Lazarus provides a comprehensive but brief overview of his influential multimodal approach with a particular focus on ways to "cut to the chase" in psychotherapy. Cutting to the chase is not a new idea for Lazarus for, as he writes, "The multimodal approach has always been relatively brief, but in the present era of managed health care, the need for even greater brevity has become a necessity" (1997, p. 124). Although much of the material assembled in this book has appeared previously in numerous articles, book chapters, and in The Practice of Multimodal Therapy: Systematic. Comprehensive and Effective Psychotherapy (1981, reprinted in 1989), this is Lazarus' s first attempt to provide an updated, book-length overview of his approach since the publication of the 1981 volume. In addition to an overview of the multimodal approach, including a discussion of newer techniques and ideas not included in the 1981 book (e.g., bridging and tracking), this book also includes a number of new case studies. Also included are appendices containing an updated version of Lazarus' useful clinical selfreport tool, the Multimodal Life History Inventory, as well as the Structural Profile Inventory, the Expanded Structural Profile, the Marital Satisfaction Questionnaire (Revised), and a copy of a Lazarus article on eclecticism and psychotherapy integration (Lazarus, 1995). Lazarus is perhaps best known for his approach to problem assessment in psychotherapy. He has argued that the conventional cognitive-behavioral approach to assessment, which focuses on affects, behaviors, and cognitions (the "ABC" model) should be broadened to include attention to bodily sensations, imagery, interpersonal relationships, and the biological dimension. The catchy acronym, BASIC-ID (for Behaviors, Affects, Sensations, Imagery, Cognition, Interpersonal, and the biological dimension or "Drugs"), summarizes Lazarus's assessment model. The BASIC-ID assessment framework is widely known and is presented in many popular counseling and psychotherapy textbooks (e.g., Cormier & Cormier, 1991). By increasing our attention to such crucial factors as the interpersonal and biological dimensions of human functioning, Lazarus has done cognitive-behavioral therapy a great service. Lazarus (chapter 1) provides an introduction to and a succinct rationale for the BASIC-ID assessment model. This chapter also includes a list of eight issues that should be addressed if therapy is to be both short term and comprehensive (p. 9) and has a useful list of 12 questions that should be addressed in the initial interview (p. 10). Chapters 2 through 5 discuss the theoretical basis and history of Lazarus's multimodal approach. A case study in chapter 3 illustrates the application of the BASIC-ID in a multimodal problem assessment process. A very brief theoretical basis for the multimodal approach is provided, and other topics, such as technical eclecticism, are discussed. Two short chapters, 5 and 6, are devoted to the finer points of multimodal problem assessment. In chapter 5, Lazarus describes two multimodal techniques, bridging and tracking, which awe during assessment as well as treatment. Bridging refers to the process of gently guiding the client from a discussion in a comfortable modality (for example, the cognitive modality) to a modality in which the client feels less comfortable (for example, the affective modality). Tracking refers to the assessment of the client's tendency to go through a predictable sequence of modalities in problematic situations. Lazarus states that most clients appear to have a typical "firing order" so that, for example, in one client with panic attacks, a typical attack might begin in the imagery modality (e. …

Inexpensive multi-mode satellite tracking feed antenna

A design of an inexpensive multi-mode tracking feed antenna, for a circularly polarised signal is described. It uses the TE11 and TM01 modes, in a smooth circular waveguide, to obtain the sum and difference patterns. The higher order mode, TM01 generated within the feed is separated from the dominant mode, TE11 by using the resonant mode filter printed on a thin dielectric material. The design of the resonant mode filter is described in some detail. The use of a printed resonant ring with a dual mode horn makes the design particularly inexpensive. Sum and difference patterns with both the dual mode and the corrugated horn are presented for comparison.