Tracking and Pedestrain Paper Reads

Paper #1 - Object Tracking for Autonomous Driving Systems
keynotes

• The Different components of Autonomous driving System

I'm keen on Tracking - Prediction - Planning aspects
MOT - Multiple Object Tracking

• Record and track moving objects over time
• In Autonomous System tracking cars, pedestrians, signals, passing vehicles everything is key

Deep Learning in Video Multi-Object Tracking

• Detection - Object Detection, Bounding boxes
• Feature Extraction - CNN or Siamese networks employed
• Affinity - Cosine Similarity, Euclidean distance, Intersection over union
• Association - Matching trackets

Real-world challenges

• Camera Motion
• Occlusions

Deep Sort - DeepSORT extends SORT by incorporating appearance information for each tracked object into the affinity stage. The underlying Kalman filter and target state definition are unchanged, but a convolutional feature extraction model is used to process bounding box crops of targets into feature vectors

Novelty
Distractor-Aware Siamese Region Proposal - Networks - DaSiamRPN is a single object tracker that combines a Siamese feature extraction network with a novel training strategy to learn distractor-aware features.

Paper #2  - Estimating Pedestrian Densities, Wait Times, and Flows with Wi-Fi and Bluetooth Sensors

Key Notes
Tracking Approaches

• Infrared, Thermal Sensors
• Bluetooth, Mobile Phones
• Automated Pedestrian Counting Technologies

Pedestrian Counting Techniques

• Anonymize, filter and aggregate traces of pedestrians
• Wifi, MAC-based approach

Paper #3 - Autonomous Vehicles that Interact with Pedestrians: A Survey of Theory and Practice
Key Notes
Different pedestrian vs Environment factors are

Decision-making Factors

SIMPLE ONLINE AND REALTIME TRACKING WITH A DEEP ASSOCIATION METRIC
Key Notes

• Simple online and realtime tracking (SORT)
• Standard Kalman filter with constant velocity motion and linear observation model
• Kalman filtering, also known as linear quadratic estimation (LQE)
• By using simple nearest neighbor queries without additional metric learning

SORT for Tracking - Git Project

Good Reads
ML6 Internship: Pedestrian tracking over multiple non-overlapping camera viewpoints

Keep Thinking!!!