SOTAVerified

Motion Detection

Motion Detection is a process to detect the presence of any moving entity in an area of interest. Motion Detection is of great importance due to its application in various areas such as surveillance and security, smart homes, and health monitoring.

Source: Different Approaches for Human Activity Recognition– A Survey

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 51–100 of 101 papers

TitleStatusHype
Inference of Upcoming Human Grasp Using EMG During Reach-to-Grasp Movement—0
UAV Images Dataset for Moving Object Detection from Moving CamerasCode1
A Robust Road Vanishing Point Detection Adapted to the Real-World Driving ScenesCode0
Which K-Space Sampling Schemes is good for Motion Artifact Detection in Magnetic Resonance Imaging?—0
Geometric Change Detection in Digital Twins using 3D Machine Learning—0
A Similarity-preserving Neural Network Trained on Transformed Images Recapitulates Salient Features of the Fly Motion Detection Circuit—0
Enabling energy efficient machine learning on a Ultra-Low-Power vision sensor for IoT—0
An Intelligent Non-Invasive Real Time Human Activity Recognition System for Next-Generation Healthcare—0
Anomalous Motion Detection on Highway Using Deep LearningCode0
Development of a skateboarding trick classifier using accelerometry and machine learningCode0
Drosophila-Inspired 3D Moving Object Detection Based on Point Clouds—0
Any Motion Detector: Learning Class-agnostic Scene Dynamics from a Sequence of LiDAR Point Clouds—0
Multimodal and multiview distillation for real-time player detection on a football fieldCode1
Spike-FlowNet: Event-based Optical Flow Estimation with Energy-Efficient Hybrid Neural NetworksCode1
RPCA-Based High Resolution Through-the-Wall Human Motion Detection and Classification—0
A Time-Delay Feedback Neural Network for Discriminating Small, Fast-Moving Targets in Complex Dynamic Environments—0
Automated Analysis of Femoral Artery Calcification Using Machine Learning Techniques—0
A Similarity-preserving Network Trained on Transformed Images Recapitulates Salient Features of the Fly Motion Detection Circuit—0
WiFi Motion Detection: A Study into Efficacy and Classification—0
A Robust Visual System for Small Target Motion Detection Against Cluttered Moving Backgrounds—0
Visual Cue Integration for Small Target Motion Detection in Natural Cluttered Backgrounds—0
Can Transfer Entropy Infer Information Flow in Neuronal Circuits for Cognitive Processing?—0
Model-free Tracking with Deep Appearance and Motion Features Integration—0
An Efficient Optical Flow Based Motion Detection Method for Non-stationary Scenes—0
Action and intention recognition of pedestrians in urban traffic—0
Unsupervised Online Video Object Segmentation with Motion Property UnderstandingCode0
WisenetMD: Motion Detection Using Dynamic Background Region Analysis—0
A Robust Background Initialization Algorithm with Superpixel Motion Detection—0
A Feedback Neural Network for Small Target Motion Detection in Cluttered Backgrounds—0
Comparative study of motion detection methods for video surveillance systemsCode0
Evolution leads to a diversity of motion-detection neuronal circuits—0
Learning-Based Quality Control for Cardiac MR Images—0
Event-based Moving Object Detection and Tracking—0
Real-Time Automatic Fetal Brain Extraction in Fetal MRI by Deep LearningCode0
MODNet: Moving Object Detection Network with Motion and Appearance for Autonomous Driving—0
Independent Motion Detection with Event-driven Cameras—0
Multi-Class Model Fitting by Energy Minimization and Mode-SeekingCode0
Change Detection under Global Viewpoint Uncertainty—0
An Analysis of Parallelized Motion Masking Using Dual-Mode Single Gaussian ModelsCode0
A Novel Motion Detection Method Resistant to Severe Illumination Changes—0
Multi-Scale Saliency Detection using Dictionary Learning—0
Automatic detection of moving objects in video surveillance—0
Deep Learning for Detecting Multiple Space-Time Action Tubes in Videos—0
“Eyes Open – Eyes Closed” EEG/fMRI data set including dedicated “Carbon Wire Loop” motion detection channels—0
Randomized Low-Rank Dynamic Mode Decomposition for Motion Detection—0
Tracking Motion and Proxemics using Thermal-sensor Array—0
On a spatial-temporal decomposition of the optical flow—0
Semantic Motion Segmentation Using Dense CRF Formulation—0
Abrupt Motion Tracking via Nearest Neighbor Field Driven Stochastic Sampling—0
Multiple-object tracking in cluttered and crowded public spaces—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1FastFlowNet (Kitti)F1 (%)92.9—Unverified
2Raft (Kitti)F1 (%)89.5—Unverified