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Found 13 papers, 8 papers with code
Recognizing Involuntary Actions from 3D Skeleton Data Using Body States
This method introduces the definition of body states and then every action is modeled as a sequence of these states.
Simultaneous Joint and Object Trajectory Templates for Human Activity Recognition from 3-D Data
The availability of low-cost range sensors and the development of relatively robust algorithms for the extraction of skeleton joint locations have inspired many researchers to develop human activity recognition methods using the 3-D data.
Human Activity Recognition
Human-Object Interaction Detection
A Fusion-based Gender Recognition Method Using Facial Images
This paper proposes a fusion-based gender recognition method which uses facial images as input.
Pixel-Level Alignment of Facial Images for High Accuracy Recognition Using Ensemble of Patches
The geometry alignment is performed pixel-wise, i. e., every pixel of the face is corresponded to a pixel of the reference face.
Fisherposes for Human Action Recognition Using Kinect Sensor Data
The proposed regularized Mahalanobis distance metric is used in order to recognize both the involuntary and highly made-up actions at the same time.
Tree-Based Optimization: A Meta-Algorithm for Metaheuristic Optimization
The experimental results on several well-known benchmarks show the outperforming performance of TBO algorithm in finding the global solution.
DTW-Merge: A Novel Data Augmentation Technique for Time Series Classification
The main challenge in training deep neural networks is the lack of sufficient data to improve the model's generalization and avoid overfitting.
Temporal Action Localization Using Gated Recurrent Units
In this paper, we propose a new network based on Gated Recurrent Unit (GRU) and two novel post-processing methods for TAL task.
Temporal Analysis of Functional Brain Connectivity for EEG-based Emotion Recognition
EEG signals in emotion recognition absorb special attention owing to their high temporal resolution and their information about what happens in the brain.
Elderly Fall Detection Using CCTV Cameras under Partial Occlusion of the Subjects Body
Experiments show that the proposed method can improve the classification accuracy by 36% for a non-deep model and 55% for a deep model in occlusion conditions.
Face: Fast, Accurate and Context-Aware Audio Annotation and Classification
This paper presents a context-aware framework for feature selection and classification procedures to realize a fast and accurate audio event annotation and classification.
Ranked #2 on
Environmental Sound Classification
on UrbanSound8K
(Accuracy metric)
Video alignment using unsupervised learning of local and global features
We introduce an unsupervised method for alignment that uses global and local features of the frames.
Dynamic Changes of Brain Network during Epileptic Seizure
Epilepsy is a neurological disorder identified by sudden and recurrent seizures, which are believed to be accompanied by distinct changes in brain dynamics.
