Motion Detection
19 papers with code • 1 benchmarks • 2 datasets
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
Benchmarks
These leaderboards are used to track progress in Motion Detection
| Trend | Dataset | Best Model | Paper | Code | Compare |
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nuScenes
KITTI'15 MSplus
Most implemented papers
An Analysis of Parallelized Motion Masking Using Dual-Mode Single Gaussian Models
Successful systems have used Gaussian Models to discern background from foreground in an image (motion from static imagery).
Multi-Class Model Fitting by Energy Minimization and Mode-Seeking
The move replaces a set of labels with the corresponding density mode in the model parameter domain, thus achieving fast and robust optimization.
Real-Time Automatic Fetal Brain Extraction in Fetal MRI by Deep Learning
We aimed to develop a fully automatic segmentation method that independently segments sections of the fetal brain in 2D fetal MRI slices in real-time.
Comparative study of motion detection methods for video surveillance systems
The objective of this study is to compare several change detection methods for a mono static camera and identify the best method for different complex environments and backgrounds in indoor and outdoor scenes.
Unsupervised Online Video Object Segmentation with Motion Property Understanding
Moreover, our method achieves better performance than the best unsupervised offline algorithm on the DAVIS-2016 benchmark dataset.
A Robust Visual System for Small Target Motion Detection Against Cluttered Moving Backgrounds
The directional contrast and the extracted motion information by the motion pathway are integrated in the mushroom body for small target discrimination.
Spike-FlowNet: Event-based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks
chan8972/Spike-FlowNet
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ECCV 2020
Spiking Neural Networks (SNNs) serve as ideal paradigms to handle event camera outputs, but deep SNNs suffer in terms of performance due to the spike vanishing phenomenon.
Multimodal and multiview distillation for real-time player detection on a football field
cioppaanthony/multimodal-multiview-distillation
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As an alternative, we developed a system that detects players from a unique cheap and wide-angle fisheye camera assisted by a single narrow-angle thermal camera.
Development of a skateboarding trick classifier using accelerometry and machine learning
Nkluge-correa/skateboarding-trick-classifier
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Introduction: Skateboarding is one of the most popular cultures in Brazil, with more than 8. 5 million skateboarders.
Anomalous Motion Detection on Highway Using Deep Learning
harpreets652/highway-traffic-anomaly
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The advent of self-driving cars provides an opportunity to apply visual anomaly detection in a more dynamic application yet no dataset exists in this type of environment.
