590AC_WK2_Lec_1_Sensing_Recognition_Part1(3).ppt

590AC_WK2_Lec_1_Sensing_Recognition_Part1(3).ppt - CMPSCI...

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CMPSCI 590AC 2-1 1 590AC 2-1 Week 2: Lecture 1 Sensing & Recognition of Emotions by Machines (Part 1) July 18, 2016
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CMPSCI 590AC 2-1 2 Movellan et al. http://mplab.ucsd.edu/
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CMPSCI 590AC 2-1 3 Readings Picard, 1997; “Affective Computing” Overview of affective signals and systems Chapter 5 T echniques for emotion sensing & recognition, synthesis & expression Chapters 6 & 7 Framework for organizing techniques for emotion sensing, recognition & expression Hudlicka, 2005: Affect Sensing and Recognition: State-of-the- Art Overview (on B’board) Picard, 2000. Toward computers that recognize and respond to user emotion. IBM Systems Journal, 39 (3-4), 705-719. (on B’board)
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CMPSCI 590AC 2-1 4 Optional Readings There are a number of optional supplemental readings (see updated syllabus) You are not expected to read these, but I encourage you to glance at the papers, to get a sense of the detailed processes involved in emotion recognition
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CMPSCI 590AC 2-1 5 Homework Homework #3: (Due 7-22, 8am) Posted on B’board in the “Homeworks” folder Email me with any questions & feel free to post questions & thoughts on the Discussion board
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CMPSCI 590AC 2-1 6 Outline for Lectures 1 & 2 Overview of emotion recognition & its applications Common framework for emotion recognition & expression Multi-modal emotion signatures Semantic primitives for different expressive channels Emotion recognition in detail Sensors & data filtering Extraction of features & semantic primitives Pattern recognition & classification algorithms Ethical issues Summary & Challenges
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CMPSCI 590AC 2-1 7 Outline for Lecture 1 (July-18) Overview of emotion recognition & its applications Common framework for emotion recognition & expression Multi-modal emotion signatures Semantic primitives for different expressive channels
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CMPSCI 590AC 2-1 8 Outline for Lecture 2 (July 20) Emotion recognition in detail Sensors & data filtering Extraction of features & semantic primitives Pattern recognition & classification algorithms Ethical issues Summary & Challenges
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CMPSCI 590AC 2-1 9 How is Emotion Recognition Useful? Enhances a range of human-computer interaction contexts Intelligent tutoring systems Adapt to student’s level of frustration Decision-support systems Adapt to decision-maker’s stress level Affective gaming Adapt game to player’s emotional state (+ or -) to increase or reduce game complexity Intelligent virtual helper or coach agent Adapt content & presentation to user’s emotional state
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Detecting Driver Stress Detecting Driver Stress Healey & Picard, MIT
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CMPSCI 590AC 2-1 11 Sensing & Recognizing Emotions Inherently difficult due to: Frequently subtle nature of emotions Variability across individuals Variability within individuals across time… & context Intrusive / expensive sensors… less so now Noisy, cluttered sensor data Computational demands of classification algorithms BUT - Significant progress made over the past 20 years
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CMPSCI 590AC 2-1 12
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