1. Vehicle detection and localization
Pei-Hen Hung
Media IC & System Lab

2. Intelligent Transportation System
Benefits of M2M in ITS
Expansion of sensor coverage/Increase of time allowed to react
Goal: Develop a proactive driver assistance system
Driver behavior modeling and inference
M2M-based neighbor map building

3. Sensor Fusion

4. Visual Analysis Subsystem Development
A Complete Vehicle Detection on RSU
Background subtraction
Feature extraction
Grand data training and classifier
Map calculation
Detection in challenging conditions
Distributed Video Benchmarking
Preparation
Device collection and testing
Campus testing
Ground truth testing/Calibration /Timing synchronization
On-road testing
Grand data collection

5. Methodology

6. Methodology
Background subtraction using Gaussian of Mixture Model (GMM)

7. Histograms of edge orientations
Methodology
Histogram of Orientated Gradient (HoG ) Feature Extraction
8*8 cell size
Histograms of edge orientations
edge
[-1, 0, 1] gradient filter
with no smoothing
8*16 cells
9 unsighted bins=>
9 dimension vector

8. Methodology Training Stage Testing Stage
Labeling target objects and extract features
SVM training
Testing Stage
SVM testing

9. Data collection 長興街&芳蘭路口 4 Camera 1 Lidar 3 Scooter with GPS
1 Scooter with Lidar and GPS

10. RSU RSU Car RSU RSU Robot Car
Scooter
Car
RSU
RSU
Robot
Scooter
Car

11. Demo

12. Event Object Signal Future work Two men walked in the office…
Objects in the Video
Conventional
Scalability
I(x,y,t)

13. Thank you