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Multimedia Specification Design and Production

Multimedia Specification Design and Production. 201 3 / Semester 2 / week 8 Lecturer: Dr. Nikos Gazepidis gazepidis@ist.edu.gr. Multimedia and HCI. Outline Human Computer Interface. Multimedia interfaces and applications. Vision based interfaces

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Multimedia Specification Design and Production

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  1. Multimedia Specification Design and Production 2013 / Semester 2 / week 8 Lecturer: Dr. Nikos Gazepidis gazepidis@ist.edu.gr

  2. Multimedia and HCI • Outline • Human Computer Interface. • Multimedia interfaces and applications. • Vision based interfaces • Systems using vision based interfaces. • Some basic methods in vision interfaces • Background subtraction. • Color blob detection and tracking. • Face detection (Viola and Jones face detector). 2

  3. Multimedia and HCI • Human Computer Interface • Different meanings of HCI: • The study of people, computer technology and the ways they interactive with each other. • The design, evaluation and implementation of computer systems for human use. • The research to study how to make computer systems more use-able. 3

  4. Multimedia and HCI • Aspects of HCI • Design • Intuition, experiences and design principles. • Human factors • Experiments testing the perception, memory and cognition models of human being. • Devices • Physical devices such as mouse, keyboards and other fancy HCI hardware. • Software and systems • Such as windows GUI, shell commands in Unix etc. 4

  5. Multimedia and HCI • HCI Studies • Computers • What are they good at and bad at? • Input, output, processing, networking, etc. • People • What are people good at? • What is the limitation of human abilities? • Input, output, memory, perception and cognition model. • No average answer. Must accommodate diversities. • Usability • More than the size of widgets, where are the buttons and syntax of commands. • Context • Environment, physical constraints, cognition constraints, task, etc. 5

  6. Multimedia and HCI • The quality of HCI • There are fives factors that affect the design and implementation of HCI • Time to learn. • Speed of performance. • Rate of errors. • Retention over time. • Subjective satisfaction 6

  7. Multimedia and HCI • Multimedia Interfaces • Multimedia interface combines different sorts of media modalities to achieve more natural and more efficient human computer communication. • Speech, audio, touch, video input (patterns, posture, gesture) etc. • “Put that there” is an example multimedia HCI that combines speech, gestures and graphics Put that there, MIT 1981 http://www.media.mit.edu/speech/sig_videos.html 7

  8. Multimedia and HCI • Advantages of Multimedia Interface • More alternative methods. • The flexibility of combining different schemes. • More efficient for specific tasks. • Greater precision of information. • Help handicapped people to use computers Virtual Reality Pen gesture interface http://www.youtube.com/watch?v=d7eGypGOlOc&feature=related http://www.youtube.com/watch?v=Gnq-8iaOcXk 8

  9. Multimedia and HCI • Vision Based Interfaces • Vision based interfaces uses computer vision techniques to achieve more effective HCI. • Vision based interfaces are based on techniques such as: Hand tracking, Hand gesture, Arm gesture Hand Pointing Face detection Head tracking Gaze Expression Lip reading Posture, body gesture and action recognition 9

  10. Multimedia and HCI Example Systems Motion Capturing 10

  11. Multimedia and HCI Example Systems (cont.) The MIT Kidsroom Posture recognition Action detection 11

  12. Multimedia and HCI Methods in Vision Interfaces • Background subtraction • Estimating the background B(n) = B(n)*alpha + I(n)*(1-alpha) Foreground Map = |Image – Background|>threshold alpha is a positive floating point number close to 1. 12

  13. Multimedia and HCI Mean Shift Tracking Result http://www.caip.rutgers.edu/~comanici/Papers/KernelTracking.pdf 13

  14. Multimedia and HCI Viola and Jones face detector • The Viola – Jones object detection framework is the first object detection framework to provide competitive object detection rates in real-time proposed in 2001 by Paul Viola and Michael Jones. • Although it can be trained to detect a variety of object classes, it was motivated primarily by the problem of face detection. This algorithm is implemented in OpenCV as cvHaarDetectObjects(). 14

  15. Multimedia and HCI Viola and Jones face detector (cont.) These features can be computed using integral images similarly to the color histograms discussed before. 15

  16. Multimedia and HCI Summary • We only touch the very surface of multimedia interfaces. • Currently, the dominant HCI is still GUI with keyboard and mouse. • Multimedia interfaces are beginning to attract more and more interests. • We need more robust and efficient media recognition schemes to support effective multimedia interfaces. 16

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