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23
An Introduction to inertial and visual sensing
- The International Journal of Robotics
, 2007
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H and Zhou H (2007) Integration of vision and inertial sensors for 3D arm motion tracking in home-based rehabilitation
- The International Journal of Robotics Research
"... The integration of visual and inertial sensors for human motion tracking has attracted significant attention recently, due to its robust performance and wide potential application. This paper introduces a real-time hybrid solution to articulated 3D arm motion tracking for home-based rehabilitation b ..."
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Cited by 19 (1 self)
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The integration of visual and inertial sensors for human motion tracking has attracted significant attention recently, due to its robust performance and wide potential application. This paper introduces a real-time hybrid solution to articulated 3D arm motion tracking for home-based rehabilitation by combining visual and inertial sen-sors. Data fusion is a key issue in this hybrid system and two dif-ferent data fusion methods are proposed. The first is a determinis-tic method based on arm structure and geometry information, which is suitable for simple rehabilitation motions. The second is a proba-bilistic method based on an Extended Kalman Filter (EKF) in which data from two sensors is fused in a predict-correct manner in order to deal with sensor noise and model inaccuracy. Experimental results are presented and compared with commercial marker-based systems, CODA and Qualysis. They show good performance for the proposed solution. KEY WORDS—sensor fusion, extended Kalman filter, iner-tial sensor, human motion tracking, home-based rehabilitation 1.
Virtual Reality System with Integrated Sound Field Simulation and Reproduction
, 2007
"... A real-time audio rendering system is introduced which combines a full room-specific simulation, dynamic crosstalk cancellation, and multitrack binaural synthesis for virtual acoustical imaging. The system is applicable for any room shape (normal, long, flat, coupled), independent of the a priori as ..."
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Cited by 17 (1 self)
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A real-time audio rendering system is introduced which combines a full room-specific simulation, dynamic crosstalk cancellation, and multitrack binaural synthesis for virtual acoustical imaging. The system is applicable for any room shape (normal, long, flat, coupled), independent of the a priori assumption of a diffuse sound field. This provides the possibility of simulating indoor or outdoor spatially distributed, freely movable sources and a moving listener in virtual environments. In addition to that, near-tohead sources can be simulated by using measured near-field HRTFs. The reproduction component consists of a headphone-free reproduction by dynamic crosstalk cancellation. The focus of the project is mainly on the integration and interaction of all involved subsystems. It is demonstrated that the system is capable of real-time room simulation and reproduction and, thus, can be used as a reliable platform for further research on VR applications.
Efficient camera motion and 3d recovery using an inertial sensor
- In Computer and Robot Vision, 2007. CRV ’07. Fourth Canadian Conference on
, 2007
"... This paper presents a system for 3D reconstruction us-ing a camera combined with an inertial sensor. The sys-tem mainly exploits the orientation obtained from the iner-tial sensor in order to accelerate and improve the matching process between wide baseline images. The orientation fur-ther contribut ..."
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Cited by 5 (0 self)
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This paper presents a system for 3D reconstruction us-ing a camera combined with an inertial sensor. The sys-tem mainly exploits the orientation obtained from the iner-tial sensor in order to accelerate and improve the matching process between wide baseline images. The orientation fur-ther contributes to incremental 3D reconstruction of a set of feature points from linear equation systems. The processing can be performed online while using consecutive groups of three images overlapping each other. Classic or incremen-tal bundle adjustment is applied to improve the quality of the model. Test validation has been performed on object and camera centric sequences. 1
A Novel Sensing and Data Fusion System for 3-D Arm Motion Tracking in Telerehabilitation
"... Abstract—In this paper, we present a novel sensing and data fusion system to track 3-D arm motion in a telerehabilitation program. A particle filter (PF) algorithm is adopted in the system to fuse data from inertial and visual sensors in a probabilistic manner. It is able to propagate multimodal dis ..."
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Cited by 5 (1 self)
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Abstract—In this paper, we present a novel sensing and data fusion system to track 3-D arm motion in a telerehabilitation program. A particle filter (PF) algorithm is adopted in the system to fuse data from inertial and visual sensors in a probabilistic manner. It is able to propagate multimodal distributions of system states based on an “importance sampling ” technique by using sets of weighted particles. To avoid the problem of conventional PF algorithms that suffer from particle degeneracy and perform poorly in a narrow distribution situation, we adopt two strategies in our system, namely state space pruning and an arm physical geometry constraint. Experimental results show that the proposed PF framework outperforms other fusion methods and provides accurate results in comparison to the ground truth. Index Terms—Biomedical measurements, particle filter (PF), sensor fusion, telerehabilitation, upper limb pose estimation, 3-D arm motion tracking. I.
Object-centered Feature Selection for Weakly-Unsupervised Object Categorization
"... We describe a novel approach of spatio-temporal mapping of local image features, to reduce the number of input data for further object categorization. The main focus of our work is the selection of good features to learn, by achieving a precise mapping of image features either related to static obje ..."
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We describe a novel approach of spatio-temporal mapping of local image features, to reduce the number of input data for further object categorization. The main focus of our work is the selection of good features to learn, by achieving a precise mapping of image features either related to static objects or to background. This can be done by initial camera motion estimation, subsequent structure estimation and final clustering of the 3D points. Experimental results show that our method achieves a significant reduction of processed image features, which yields a better performance in subsequent learning modules. 1
Autonomous Vehicle Video Aided Navigation – Coupling INS and Video Approaches
"... Abstract. As autonomous vehicle systems become more prevalent, their navigation capabilities become increasingly critical. Currently most systems rely on a combined GPS/INS solution for vehicle pose computation, while some systems use a video-based approach. One problem with a GPS/INS approach is th ..."
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Abstract. As autonomous vehicle systems become more prevalent, their navigation capabilities become increasingly critical. Currently most systems rely on a combined GPS/INS solution for vehicle pose computation, while some systems use a video-based approach. One problem with a GPS/INS approach is the possible loss of GPS data, especially in urban environments. Using only INS in this case causes significant drift in the computed pose. The video-based approach is not always reliable due to its heavy dependence on image texture. Our approach to autonomous vehicle navigation exploits the best of both of these by coupling an outlier-robust video-based solution with INS when GPS is unavailable. This allows accurate computation of the system’s current pose in these situations. In this paper we describe our system design and provide an analysis of its performance, using simulated data with a range of different noise levels. 1
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Permissions: Requests for permissions to reproduce figures, tables, or portions of articles originally published in Circulation can be obtained via RightsLink, a service of the Copyright Clearance Center, not the Editorial Office. Once the online version of the published article for which permission is being requested is located, click Request Permissions in the middle column of the Web page under Services. Further information about this process is available in the Permissions and Rights Question and Answer document. Reprints: Information about reprints can be found online at:
