Multi Object Tracking

AI-Powered
Multi-Object Detector and Tracker

Object Detection

Deep learning based Real-time Object Detection

Object Tracking

Deep learning based tracker trough Multi-camera View

Object Detection

• A deep learning-based approach

• Based on the state-of-art detectors

• Robust (trained on the dataset with noise, masking, corruption)

• Acceptable Accurate

• Support different type of Objects

• Tested on different Object such as Pedestrians and Vehicles

• Our detector needs optimization for processing time

Object Classifier

• Based on SimpleNet and Efficient Net

• Near Real-time

• Accurate enough (about 95%)

• Robust against camera changes, light conditions, weather conditions,etc

Multi-Object Tracker

• • Combining Tracking and Detection

  • Multi-object Tracker

  • Online learning (learning based)

  • Real-time tracker

  • CNN-based feature extractor and using Triplet-loss

  • Using Kalman filter for Motion Estimation

Scalability and Quality Assurance

• The solution is highly scalable and can be used in several applications

• It does not depend on the camera type, position or situation

• The same solution can be applied in the similar scenarios