Using a 3D CNN for Rejecting False Positives on Pedestrian Detection.
Francisco Gomez-DonosoEdmanuel CruzMiguel CazorlaStewart WorrallEduardo M. NebotPublished in: IJCNN (2020)
Keyphrases
- false positives
- pedestrian detection
- detection rate
- cellular neural networks
- false negative
- false positive rate
- human body
- false alarms
- human detection
- number of false positives
- true positive
- occlusion handling
- object detection
- low false positive rate
- pedestrian tracking
- histograms of oriented gradients
- benchmark datasets
- data mining
- high detection rate
- cascade classifier
- support vector machine
- three dimensional