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Local shape descriptor selection for object recognition in range data
Local shape descriptor selection for object recognition and localization in range data is formulated herein as an optimization problem. Local shape descriptors are used for establishing pointExpand
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Difference of Normals as a Multi-scale Operator in Unorganized Point Clouds
A novel multi-scale operator for unorganized 3D point clouds is introduced. The Difference of Normals (DoN) provides a computationally efficient, multi-scale approach to processing large unorganizedExpand
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Autonomous Unobtrusive Detection of Mild Cognitive Impairment in Older Adults
The current diagnosis process of dementia is resulting in a high percentage of cases with delayed detection. To address this problem, in this paper, we explore the feasibility of autonomouslyExpand
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Dynamic parameter identification and analysis of a PHANToM haptic device
In this paper, the dynamics of a SensAble Technologies PHANToM Premium 1.5 haptic device is experimentally identified and analyzed. Towards this purpose, the dynamic model derived in the work of M.Expand
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3D Human Motion Analysis to Detect Abnormal Events on Stairs
Falls on the stairs are a common cause of accidental injury among the older adults. Understanding the mechanisms leading to such accidents may improve not only the prevention of falls, but alsoExpand
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Use of Accelerometer-Based Feedback of Walking Activity for Appraising Progress With Walking-Related Goals in Inpatient Stroke Rehabilitation
Background. Regaining independent ambulation is important to those with stroke. Increased walking practice during “down time” in rehabilitation could improve walking function for individuals withExpand
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Variable Dimensional Local Shape Descriptors for Object Recognition in Range Data
We propose a new set of highly descriptive local shape descriptors (LSDs) for model-based object recognition and pose determination in input range data. Object recognition is performed in threeExpand
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Vision-based assessment of gait features associated with falls in people with dementia.
BACKGROUND Gait impairments contribute to falls in people with dementia. In this study, we use a vision-based system to record episodes of walking over a two week period as participants movedExpand
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Towards a single sensor passive solution for automated fall detection
Falling in the home is one of the major challenges to independent living among older adults. The associated costs, coupled with a rapidly growing elderly population, are placing a burden onExpand
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Detecting unseen falls from wearable devices using channel-wise ensemble of autoencoders
  • S. Khan, B. Taati
  • Computer Science, Mathematics
  • Expert Syst. Appl.
  • 12 October 2016
Abstract A fall is an abnormal activity that occurs rarely, so it is hard to collect real data for falls. It is, therefore, difficult to use supervised learning methods to automatically detect falls.Expand
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