Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Computer Vision in the Age of IoT

21 views

Published on

ICPR 2014 Invited Speech

Published in: Education
  • Be the first to comment

  • Be the first to like this

Computer Vision in the Age of IoT

  1. 1. COMPUTER VISION IN THE AGE OF IOT FROM BIG DATA TO SYSTEM SELF-AWARENESS YUAN-KAI WANG FU-JEN CATHOLIC UNIVERSITY 2014/8/26 Plenary speech in International Conference on Pattern Recognition, Stockholm, Sweden.1
  2. 2. 2 Healthcare Smart HomeEntertainment Security Transportation Industrial Others Internet of Things Retails
  3. 3. 3
  4. 4. IoC Challenges 4 •  IoC is closely related to camera networks, which becomes a large-scale system. •  System-level thinking is necessary •  Academic expertise on algorithms, such as computer vision and pattern recognition, are important for accuracy, efficiency and convenience. •  Industrial concerns on system integration are critical for configuration, maintenance and management. •  Autonomic computing with self-awareness •  Paul Horn, 2001. •  Camera collaboration of anomaly events
  5. 5. Our Experience Wide-Area Video Surveillance in Campus 5
  6. 6. Video Surveillance Cloud 6 Intrusion detection PTZ pedestrian tracking Camera anomaly detection Video Synopsis Geographical visualizationMulti-resolution fusion and visualization Parking lots estimation Illegal parking detection Video based face extraction Storage Area Network PC Mobile device Multi-core Hypervisor GPGPU Yuan-Kai Wang et al. "A Large Scale Video Surveillance System with Heterogeneous Information Fusion and Visualization for Wide Area Monitoring," IEEE Int. Conf. IIHMSP, 2012.
  7. 7. Our Implementation 7
  8. 8. System Self-Awareness 8 Fault awareness Environment awareness Context awareness
  9. 9. Camera Anomaly Detection: Self-awareness of Camera 9 Yuan-Kai Wang et al. "Real-Time Camera Anomaly Detection for Real-World Video Surveillance," ICMLC, 2011. Normal Anomaly! Background updating graph cut Online Kalman filter finite state machine Features of image quality and replacement
  10. 10. Traffic Camera Anomaly Detection Yuan-Kai Wang et al. "Traffic Camera Anomaly Detection," ICPR 2014. (8/28, Balcony Level5, PM 4:00-5:40, paper no. : ThCT4p.26) 10
  11. 11. 11
  12. 12. Related Publications "  "A Large Scale Video Surveillance System with Heterogeneous Information Fusion and Visualization for Wide Area Monitoring," IEEE International Conference on Intelligent Information Hiding and Multimedia Signal Processing, 2012. "  "Real-Time Camera Anomaly Detection for Real-World Video Surveillance," International Conference on Machine Learning and Cybernetics, 2011. "  "Traffic Camera Anomaly Detection," ICPR 2014. (8/28, Balcony Level5, PM 4:00-5:40, paper no. : ThCT4p.26) 12

×