AIMC Topic: Motion

Clear Filters Showing 291 to 300 of 879 articles

Topographic design in wearable MXene sensors with in-sensor machine learning for full-body avatar reconstruction.

Nature communications
Wearable strain sensors that detect joint/muscle strain changes become prevalent at human-machine interfaces for full-body motion monitoring. However, most wearable devices cannot offer customizable opportunities to match the sensor characteristics w...

Lite-3DCNN Combined with Attention Mechanism for Complex Human Movement Recognition.

Computational intelligence and neuroscience
Three-dimensional convolutional network (3DCNN) is an essential field of motion recognition research. The research work of this paper optimizes the traditional three-dimensional convolution network, introduces the self-attention mechanism, and propos...

Frame-rate up-conversion detection based on convolutional neural network for learning spatiotemporal features.

Forensic science international
With the advance in user-friendly and powerful video editing tools, anyone can easily manipulate videos without leaving prominent visual traces. Frame-rate up-conversion (FRUC), a representative temporal-domain operation, increases the motion continu...

Siamese network with a depthwise over-parameterized convolutional layer for visual tracking.

PloS one
Visual tracking is a fundamental research task in vision computer. It has broad application prospects, such as military defense and civil security. Visual tracking encounters many challenges in practical application, such as occlusion, fast motion an...

Concurrent validity of artificial intelligence-based markerless motion capture for over-ground gait analysis: A study of spatiotemporal parameters.

Journal of biomechanics
Gait analysis is used in research and clinical environments; yet several limitations exist in current methodologies. Markerless systems, utilizing high-speed video and artificial intelligence, eliminate most limitations encountered in marker-, depth-...

Synthesising 2D Video from 3D Motion Data for Machine Learning Applications.

Sensors (Basel, Switzerland)
To increase the utility of legacy, gold-standard, three-dimensional (3D) motion capture datasets for computer vision-based machine learning applications, this study proposed and validated a method to synthesise two-dimensional (2D) video image frames...

Adaptive Biological Neural Network Control and Virtual Realization for Engineering Manipulator.

Computational intelligence and neuroscience
By analyzing the feasibility of the digital twin technology in the assembly of construction machinery, the assembly process of the construction manipulator in the engineering environment is discussed. According to the application criteria and modelin...

Rich learning representations for human activity recognition: How to empower deep feature learning for biological time series.

Journal of biomedical informatics
Deep learning versus feature engineering has drawn significant attention specifically for applications where expertly crafted features have been used for decades. Human activity recognition is no exception where statistical and motion specific featur...

Minimize Tracking Occlusion in Collaborative Pick-and-Place Tasks: An Analytical Approach for Non-Wrist-Partitioned Manipulators.

Sensors (Basel, Switzerland)
Several industrial pick-and-place applications, such as collaborative assembly lines, rely on visual tracking of the parts. Recurrent occlusions are caused by the manipulator motion decrease line productivity and can provoke failures. This work provi...

Touchless interactive teaching of soft robots through flexible bimodal sensory interfaces.

Nature communications
In this paper, we propose a multimodal flexible sensory interface for interactively teaching soft robots to perform skilled locomotion using bare human hands. First, we develop a flexible bimodal smart skin (FBSS) based on triboelectric nanogenerator...