Human posture estimation using voxel data for "smart" airbag systems: issues and framework

Cheng, Shinko Y.; Trivedi, Mohan M.

doi:10.1109/ivs.2004.1336360

Cited by 11 publications

(8 citation statements)

References 7 publications

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“…Harada and others used pressure sensors embedded in a bed to detect postures of a bed-ridden users [22]. Several papers report using seated posture information to detect driver fatigue [18] and to deploy smart airbag systems [42,8]. Most posture recognition systems reported in literature focus on standing postures and use vision-based systems.…”

Section: Related Workmentioning

confidence: 99%

Robust, low-cost, non-intrusive sensing and recognition of seated postures

Mutlu

Krause

Forlizzi

et al. 2007

Proceedings of the 20th Annual ACM Symposium on User Interface Software and Technology

115

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In this paper, we present a methodology for recognizing seated postures using data from pressure sensors installed on a chair. Information about seated postures could be used to help avoid adverse effects of sitting for long periods of time, or to predict a user's activities as input to a humancomputer interface. Our approach to posture recognition avoids the use of expensive hardware and complex prediction algorithms while providing recognition for users, for whom the classifier is not trained, using a near-optimal sensor placement strategy. We evaluated the performance of our technology in a series of empirical evaluations including (1) cross-validation experiments (classification accuracy of 87% for ten postures), and (2) a physical deployment of our system (78% classification accuracy).

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Section: Related Workmentioning

confidence: 99%

Robust, low-cost, non-intrusive sensing and recognition of seated postures

Mutlu

Krause

Forlizzi

et al. 2007

Proceedings of the 20th Annual ACM Symposium on User Interface Software and Technology

115

View full text Add to dashboard Cite

show abstract

“…It furthers the case when head and torso positions are known. It has been shown that the head and torso can be found from the voxel data of occupants of various sizes with consistent regularity [19]. The key components for that voxelbased occupant posture estimation system are camera placement, camera calibration, silhouette generation, voxel reconstruction, and body modeling from voxel data.…”

Section: B Extension Using Sfs Voxel Datamentioning

confidence: 99%

Occupant Posture Analysis With Stereo and Thermal Infrared Video: Algorithms and Experimental Evaluation

Trivedi

Cheng

Childers

et al. 2004

IEEE Trans. Veh. Technol.

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“…Traditionally, a human body pose can be accurately reconstructed from the motion captured with optical markers attached to body parts [1]. These marker-based systems usually use multiple cameras to capture motions simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Human Pose Estimation from Monocular Images: A Comprehensive Survey

Gong

Zhang

Gonzàlez

et al. 2016

Sensors

128

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Human pose estimation refers to the estimation of the location of body parts and how they are connected in an image. Human pose estimation from monocular images has wide applications (e.g., image indexing). Several surveys on human pose estimation can be found in the literature, but they focus on a certain category; for example, model-based approaches or human motion analysis, etc. As far as we know, an overall review of this problem domain has yet to be provided. Furthermore, recent advancements based on deep learning have brought novel algorithms for this problem. In this paper, a comprehensive survey of human pose estimation from monocular images is carried out including milestone works and recent advancements. Based on one standard pipeline for the solution of computer vision problems, this survey splits the problem into several modules: feature extraction and description, human body models, and modeling methods. Problem modeling methods are approached based on two means of categorization in this survey. One way to categorize includes top-down and bottom-up methods, and another way includes generative and discriminative methods. Considering the fact that one direct application of human pose estimation is to provide initialization for automatic video surveillance, there are additional sections for motion-related methods in all modules: motion features, motion models, and motion-based methods. Finally, the paper also collects 26 publicly available data sets for validation and provides error measurement methods that are frequently used.

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Human posture estimation using voxel data for "smart" airbag systems: issues and framework

Cited by 11 publications

References 7 publications

Robust, low-cost, non-intrusive sensing and recognition of seated postures

Robust, low-cost, non-intrusive sensing and recognition of seated postures

Occupant Posture Analysis With Stereo and Thermal Infrared Video: Algorithms and Experimental Evaluation

Human Pose Estimation from Monocular Images: A Comprehensive Survey

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