AIMC Topic: Posture

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Learning and Tracking the 3D Body Shape of Freely Moving Infants from RGB-D sequences.

IEEE transactions on pattern analysis and machine intelligence
Statistical models of the human body surface are generally learned from thousands of high-quality 3D scans in predefined poses to cover the wide variety of human body shapes and articulations. Acquisition of such data requires expensive equipment, ca...

Counts of mechanical, external configurations compared to computational, internal configurations in natural and artificial systems.

PloS one
Animal movement encodes information that is meaningfully interpreted by natural counterparts. This is a behavior that roboticists are trying to replicate in artificial systems but that is not well understood even in natural systems. This paper presen...

Artificial Neural Network for in-Bed Posture Classification Using Bed-Sheet Pressure Sensors.

IEEE journal of biomedical and health informatics
Pressure ulcer prevention is a vital procedure for patients undergoing long-term hospitalization. A human body lying posture (HBLP) monitoring system is essential to reschedule posture change for patients. Video surveillance, the conventional method ...

Improved Convolutional Pose Machines for Human Pose Estimation Using Image Sensor Data.

Sensors (Basel, Switzerland)
In recent years, increasing human data comes from image sensors. In this paper, a novel approach combining convolutional pose machines (CPMs) with GoogLeNet is proposed for human pose estimation using image sensor data. The first stage of the CPMs di...

Feature Boosting Network For 3D Pose Estimation.

IEEE transactions on pattern analysis and machine intelligence
In this paper, a feature boosting network is proposed for estimating 3D hand pose and 3D body pose from a single RGB image. In this method, the features learned by the convolutional layers are boosted with a new long short-term dependence-aware (LSTD...

LCR-Net++: Multi-Person 2D and 3D Pose Detection in Natural Images.

IEEE transactions on pattern analysis and machine intelligence
We propose an end-to-end architecture for joint 2D and 3D human pose estimation in natural images. Key to our approach is the generation and scoring of a number of pose proposals per image, which allows us to predict 2D and 3D poses of multiple peopl...

3D Human Pose Machines with Self-Supervised Learning.

IEEE transactions on pattern analysis and machine intelligence
Driven by recent computer vision and robotic applications, recovering 3D human poses has become increasingly important and attracted growing interests. In fact, completing this task is quite challenging due to the diverse appearances, viewpoints, occ...

Patient 3D body pose estimation from pressure imaging.

International journal of computer assisted radiology and surgery
PURPOSE: In-bed motion monitoring has become of great interest for a variety of clinical applications. Image-based approaches could be seen as a natural non-intrusive approach for this purpose; however, video devices require special challenging setti...

Face-from-Depth for Head Pose Estimation on Depth Images.

IEEE transactions on pattern analysis and machine intelligence
Depth cameras allow to set up reliable solutions for people monitoring and behavior understanding, especially when unstable or poor illumination conditions make unusable common RGB sensors. Therefore, we propose a complete framework for the estimatio...

Toward a motor signature in autism: Studies from human-machine interaction.

L'Encephale
BACKGROUND: Autism spectrum disorder (ASD) is a heterogeneous group of neurodevelopmental disorders which core symptoms are impairments in socio-communication and repetitive symptoms and stereotypies. Although not cardinal symptoms per se, motor impa...