SRGE Workshop on Intelligent system and Application, 27 Dec. 2017 in the framework of the int. conf of computer science, information systems, and operation research, ISSR, Cairo University

1. Real-time action localization
Eng. Ahmed ali hammam
Master Student - SRGE Member
Workshop on Intelligent Systems and
Applications
SIA’17, Faculty of Computers and Information, Cairo University, Egypt23 Sep 2017

2. Overview
 Introduction
 Video Classification
 Action Classification (Recognition)
 Action Detection
 Action Localization
 Offline action localization Vs Online action localization
 Application
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SIA’17, Faculty of Computers and Information, Cairo University, Egypt

3. Introduction
Image Classification
 Input : image
 Output : label
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SIA’17, Faculty of Computers and Information, Cairo University, Egypt
Cat

4. Introduction
Image localization
 Input : image
 Output : Box
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SIA’17, Faculty of Computers and Information, Cairo University, Egypt

5. Introduction
Image Classification + Image localization
 Input : image
 Output : label + Box
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SIA’17, Faculty of Computers and Information, Cairo University, Egypt
Cat

6. Introduction
 Object Detection
 Detect all available objects
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SIA’17, Faculty of Computers and Information, Cairo University, Egypt

7. Introduction
 Object Recognition
 detect all objects Localized
them with a bounding box and
label that bounding box
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SIA’17, Faculty of Computers and Information, Cairo University, Egypt
CatDog

8. Video Classification
 treat video frames as images (image classification for every frame).
 aggregate all classification scores .
 come up with a final classification for the video .
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SIA’17, Faculty of Computers and Information, Cairo University, Egypt

9. Action Classification
 Classify the action on video (jump, Run , Walk)
 Input : video
 Output : label of the action.
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SIA’17, Faculty of Computers and Information, Cairo University, Egypt

10. Action Detection
 Detecting the actions inside the videos
 Only Show a box on the action
 Where is the action in the Video ?
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SIA’17, Faculty of Computers and Information, Cairo University, Egypt

11. Action Localization
 Where is the action in the Video ?
 What is the action in the Video ?
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SIA’17, Faculty of Computers and Information, Cairo University, Egypt

12. Offline Action Localization Vs Online Action Localization
 offline action Localization
 use of the whole video to make decisions.
 Action Detection+ Action Classification = Offline Action Localization
 online action Localization
 required to determine which actions the current frame.
 Not using future information.
 Action Detection + Action Prediction = Online Action Localization
 Processing time.
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SIA’17, Faculty of Computers and Information, Cairo University, Egypt

13. Application
 intelligent surveillance systems
 auto-monitoring of patients
 health care assistance
 Gaming
 human-computer interaction
 robotic
 vehicle accident avoidance
 criminal activity analysis
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SIA’17, Faculty of Computers and Information, Cairo University, Egypt

14. Application
 intelligent surveillance systems
 auto-monitoring of patients
 health care assistance
 Gaming
 human-computer interaction
 robotic
 vehicle accident avoidance
 criminal activity analysis
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SIA’17, Faculty of Computers and Information, Cairo University, Egypt

15. Application
 intelligent surveillance systems
 auto-monitoring of patients
 health care assistance
 Gaming
 human-computer interaction
 robotic
 vehicle accident avoidance
 criminal activity analysis
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SIA’17, Faculty of Computers and Information, Cairo University, Egypt

16. Application
 intelligent surveillance systems
 auto-monitoring of patients
 health care assistance
 Gaming
 human-computer interaction
 robotic
 vehicle accident avoidance
 criminal activity analysis
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SIA’17, Faculty of Computers and Information, Cairo University, Egypt

17. Application
 intelligent surveillance systems
 auto-monitoring of patients
 health care assistance
 Gaming
 human-computer interaction
 robotic
 vehicle accident avoidance
 criminal activity analysis
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SIA’17, Faculty of Computers and Information, Cairo University, Egypt

18. Application
 intelligent surveillance systems
 auto-monitoring of patients
 health care assistance
 Gaming
 human-computer interaction
 robotic
 vehicle accident avoidance
 criminal activity analysis
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SIA’17, Faculty of Computers and Information, Cairo University, Egypt

19. Application
 intelligent surveillance systems
 auto-monitoring of patients
 health care assistance
 Gaming
 human-computer interaction
 robotic
 vehicle accident avoidance
 criminal activity analysis
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SIA’17, Faculty of Computers and Information, Cairo University, Egypt

20. Application
 intelligent surveillance systems
 auto-monitoring of patients
 health care assistance
 Gaming
 human-computer interaction
 robotic
 vehicle accident avoidance
 criminal activity analysis
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SIA’17, Faculty of Computers and Information, Cairo University, Egypt

21. Thanks and Acknowledgement
Faculty of Computers and Information, Cairo
University, Egypt