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UTD-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and a wearable inertial sensor
- C. Chen, R. Jafari, N. Kehtarnavaz
- Computer ScienceIEEE International Conference on Image Processing…
- 10 December 2015
A freely available dataset, named UTD-MHAD, which consists of four temporally synchronized data modalities, which includes RGB videos, depth videos, skeleton positions, and inertial signals from a Kinect camera and a wearable inertial sensor for a comprehensive set of 27 human actions is described.
Real-World Anomaly Detection in Surveillance Videos
- Waqas Sultani, C. Chen, M. Shah
- Computer ScienceIEEE/CVF Conference on Computer Vision and…
- 12 January 2018
The experimental results show that the MIL method for anomaly detection achieves significant improvement on anomaly detection performance as compared to the state-of-the-art approaches, and the results of several recent deep learning baselines on anomalous activity recognition are provided.
Robust Image and Video Dehazing with Visual Artifact Suppression via Gradient Residual Minimization
A new method for reliable suppression of different types of visual artifacts in image and video dehazing is proposed and can generate results with much less visual artifacts than previous approaches for lower quality inputs such as compressed video clips.
Local Binary Patterns and Extreme Learning Machine for Hyperspectral Imagery Classification
- W. Li, C. Chen, Hongjun Su, Q. Du
- Computer ScienceIEEE Transactions on Geoscience and Remote…
- 15 January 2015
The proposed framework employs local binary patterns to extract local image features, such as edges, corners, and spots, and employs the efficient extreme learning machine with a very simple structure as the classifier.
Enhanced skeleton visualization for view invariant human action recognition
Enhanced skeleton visualization method encodes spatio-temporal skeletons as visual and motion enhanced color images in a compact yet distinctive manner and consistently achieves the highest accuracies on four datasets, including the largest and most challenging NTU RGB+D dataset for skeleton-based action recognition.
A Memory Retrieval-Extinction Procedure to Prevent Drug Craving and Relapse
A behavioral intervention that decreases drug seeking in rat models of relapse can decrease drug craving in abstinent heroin addicts and this retrieval-extinction procedure is a promising nonpharmacological method for decreasing drug craving and relapse during abstinence.
Resilient Distribution System by Microgrids Formation After Natural Disasters
- C. Chen, Jianhui Wang, F. Qiu, Dongbo Zhao
- Computer Science, EngineeringIEEE Transactions on Smart Grid
- 1 March 2016
A novel distribution system operational approach by forming multiple microgrids energized by DG from the radial distribution system in real-time operations to restore critical loads from the power outage to maximize the critical loads to be picked up.
Compressed-sensing recovery of images and video using multihypothesis predictions
- C. Chen, Eric W. Tramel, J. Fowler
- Mathematics, Computer ScienceConference Record of the Forty Fifth Asilomar…
- 1 November 2011
Experimental results demonstrate that the proposed reconstructions outperform alternative strategies not employing multihypothesis predictions, and a Tikhonov regularization to an ill-posed least-squares optimization is proposed.
PP1-mediated dephosphorylation of phosphoproteins at mitotic exit is controlled by inhibitor-1 and PP1 phosphorylation
It is reported here that protein phosphatase-1 (PP1) is the main catalyst of mitotic phosphoprotein dephosphorylation, and Cdc2 both phosphorylates multiple mitotic substrates and inhibits their PP1-mediated deph phosphorylation.
Real-time human action recognition based on depth motion maps
A l2-regularized collaborative representation classifier with a distance-weighted Tikhonov matrix is employed for action recognition, shown to be computationally efficient allowing it to run in real-time.