ArticleBehavior research methods2024
Automatic object detection for behavioural research using YOLOv8.
Article in Behavior research methods, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed.
- Automated vision-language framework for kinematic profiling and performance diagnostics in competitive swimming.BMC sports science, medicine & rehabilitation · 2026Article
- YOLOv8 computer vision for automated offside detection in professional football validated through supervised learning.Scientific reports · 2026Article
- Application of a YOLOv8-based model on lateral lumbar radiographs for screening of acute and chronic thoracolumbar fractures and osteoporosis.BMC musculoskeletal disorders · 2026Article
- Spatially Time-Based Robust Tracking and Re-Identification of Kindergarten Students: A Hybrid Deep Learning Framework Combining YOLOv8n and Vision Transformer (ViT).Journal of imaging · 2026Article
- The fundamentals of eye tracking part 6: Working with areas of interest.Behavior research methods · 2026Article
- MSDF-Net: a cross-version lightweight detection framework based on deformable convolution and high-resolution feature enhancement for pine wilt disease.Frontiers in plant science · 2026Article
- FDMB-YOLOv11: Traffic police command gesture recognition method under different lighting conditions.PloS one · 2026Article
- Distinct oxytocin populations support seismic social communication and militant behaviors in a naturally solitary wild rodent.iScience · 2025Article
- Synthetic Data Generation for AI-Based Quality Inspection of Laser Welds in Lithium-Ion Batteries.Sensors (Basel, Switzerland) · 2025Article
- GESC-YOLO: Improved Lightweight Printed Circuit Board Defect Detection Based Algorithm.Sensors (Basel, Switzerland) · 2025Article
- Gaze Zone Classification for Driving Studies Using YOLOv8 Image Classification.Sensors (Basel, Switzerland) · 2024Article
- Lightweight Corn Leaf Detection and Counting Using Improved YOLOv8.Sensors (Basel, Switzerland) · 2024Article
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Abstract
Observational studies of human behaviour often require the annotation of objects in video recordings. Automatic object detection has been facilitated strongly by the development of YOLO ('you only look once') and particularly by YOLOv8 from Ultralytics, which is easy to use. The present study examines the conditions required for accurate object detection with YOLOv8. The results show almost perfect object detection even when the model was trained on a small dataset (100 to 350 images). The detector, however, does not extrapolate well to the same object in other backgrounds. By training the detector on images from a variety of backgrounds, excellent object detection can be restored. YOLOv8 could be a game changer for behavioural research that requires object annotation in video recordings.
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