cs415 human computer interaction -...
TRANSCRIPT
October 30, 2017 Sam Siewert
CS415Human Computer Interaction
Lecture 10 – Advanced HCIUniversal Design & Intro to Cognitive
Models
Summary of Thoughts on Intelligent Transportation Systems
Collective Wisdom of Our Classes (2015, 2016, 2017)– Self driving Cars will become ubiquitous by?
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Year 2020 2025 2030 2035 2040 2045 Beyond Out of
2015 class 1 1 1 0 1 0 0 6
2016 class 0 1 3 0 1 0 0 5
2017 class 0 0 1 1 2 1 2 7
Summary of Thoughts on ITSRevolutionary vs. Evolutionary from Now to Ubiquitous
– Evolutionary [7]“Self-driving cars have to deal with personal acceptance, like the touch screens did, but these cars also have to deal with safety” … “By 2035 the (sic) millenial generation will” … “have a big push on automation and technology” … “the Baby Boomer generation will be getting to a point where they are out numbered”. “evolution of self-driving cars will be slow and steady” … “with many government and safety hoops” … “like manual transmission vehicles, modern vehicles (human driven) will stick around”“It will never become a nationwide reality” … “most people enjoy driving” … “a small percentage of the population will benefit from the technology like people with disabilities”“evolution with each generation going more towards self driving” … “contingent upon whether or not self-driving” … “does not have any large number of (sic) causulties or negative impact”“as the generations shift” … “self-driving will be the last step of this evolutionary process” … “each dealer will eventually come up with their own design”“enough time to develop software and hardware to be deemed safe” … “enough time to be deemed socially acceptable”“younger generations” … “are more comfortable with the thought of self driving” … “The key to this problem is social acceptance”
– Revolutionary [0] - No responses interpreted as revolutionary
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AssignmentsAssignment #4 – Posted, Last Practice Lab (Cameras and OpenCV)
Assignment #5 – Propose Group Project (Groups of 3)
Assignment #6 – Project
Final Oral Exam – Presentation of Project– HCI Design– Experimental Design for Usability Analysis– Prototype or Mockup of Design
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This Week … Chapter 10 – Introduction to Universal Design– Making Computers Available to Everyone– Computer Solutions for Prosthetics– Active Learning Discussion – The Human Cyborg?
Chapter 12 – Cognitive Models– GOMS – Goal, Operators, Methods and Selection– Goal - describing what the user wants to achieve– Operators - basic actions that the user must perform in order to
use the system– Methods - several ways in which a goal can be split into sub-
goals– Selection – choice of method and prediction of which will be
used
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Assignment #4Use of Digital Cameras with Embedded Linux (V4L2/UVC/USB) - OpenCV
Applications in Intelligent Transportation, Augmented Reality, Communications (e.g. Skype, Apple Facetime, WeChat)
Jetson has OpenCV installed (JetPack 3.1)
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Assignment #4 - ObjectivesPlay with the Cameras and OpenCV First– Verify Hardware– Get a Feel for Performance– Capabilities
Learn about Camera Devices and Device Interfaces
Develop a Camera Application
Consider Processing for Display and Interaction
Human Aspects – Color, Frame Rate, Segmentation
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Assignment #4 DemoReal-time Camera Scene Analysis– Uncompressed, Un-encoded Camera Frames (Not MPEG)– Transforms RGB or Graymap XY Pixel Array Into Segments and
Major Components in Frames– Eliminate Backround (Difference of Frames – Current, Historical)– Segments Analyzed (Recognition) – e.g. Gesture (Thumbs Up,
Thumbs Down)
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Segmenting Linear Elements Segmenting Circular Elements
Universal Design and Embedded HCIChapter 10 – Introduction to Universal Design– Making Computers Available to Everyone– Computer Solutions for Prosthetics– Active Learning Discussion – The Human Cyborg?
Popular NewsTed Talk on Color BlindnessTed Talk – We are Already Cyborgs
Multi-modal Systems– Speech– Audio– Touch– Handwriting– Gestures
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Minute PaperHumans have long been using tools to extend or restore physical capability, and instruments to enhance perception of the world, which fits the definition of cyborg (cyber organism).
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https://en.wiktionary.org/wiki/cyborg
Tools and instruments which progress to wearable devices, which can in turn become prosthetics, are a form of personal cybernetics, but can also be used for social networking as well as personal perception. Is this a positive and useful form of HCI? What costs, benefits, and risks do you see related?
Universal DesignDesign for Diversity– People with Sensory, Physical or Cognitive Impairment– Age Groups– Varying Cultures and Backgrounds– Localization – Languages
7 Principles of Universal Design1. Equitable Use – No User is Excluded2. Flexibility – Methods of Use, Pace, Precision, Ability3. Intuitive – Wide Range of Knowledge and Experience4. Perceptible Information – Graphic, Verbal, Text, Touch5. Error Tolerance – Minimize Impact of Mistakes (e.g. Undo)6. Low Physical Effort – Comfortable, Minimal Fatigue7. Size and Space – Sitting or Standing, Body Size, Posture,
Mobility Sam Siewert 11
SpeechGeneration – Text to Speech - SynthesisRecognition – Speech to Text, to Syntax and Semantics
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Haptic InterfacesHaptics - Touch– Cutaneous (skin tactile sensations)– Kinesthetics – movement perception and position
Current Use – Surgical Training, e.g. LapSim
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Handwriting SystemsRecord – e.g. Signatures (FedEx, UPS, DocuSign, …)AOS Swipe in Settings (Hybrid Handwriting/Typing)Recognize Input– No Systems Provide General Cursive Script Recognition– Some Success with Character at a Time Input– Apple Newton (Limited Success)
Touch Screen Typing
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Apple Newton – Stylus PDA
Gesture RecognitionCameras (Active or Passive) with Depth Mapping, Segmentation and TrackingData Gloves – Rotation (Yaw, Pitch, Roll), Translation (X,Y,Z), Rates of Translation/Rotation, and Finger Flexures
Camera Alone, Glove Alone, or Sensor Fusion
Glove is Intrusive, but Improves Accuracy
Challenge – Full Speed American Sign Language Recognition
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3D Active Computational Photometry Concept (Rev-A + TI Kit)
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AnalogCamera #1
RGB(Visible)
Altera FPGACVPU
(Computer Vision Processing Unit)
MobileSensor Network
Processor(TI OMAP, Atom)
Networked Video
Analytics
HD DigitalCamera Port(Snapshot)
USB 2.0, PCIeHost Channels
Flash SD Card
AnalogCamera #2
(Near Infrared)
TI DLP Light-crafter Kithttp://www.ti.com/tool/dlplightcrafter
Depth Map
IR Pattern Projection
https://www.cs.purdue.edu/homes/aliaga/cs635-10/lec-structured-light.pdf
Photo credits and reference:Dr. Daniel Aliaga, Purdue Universityhttps://www.cs.purdue.edu/homes/aliaga/
3D Computer Vision TransformsLong Range ( > 5 meters) Using Passive Binocular Methods– Impractical to Project from a UAV or Long Range Observer– Requires Image Registration– Accurate Camera Intrinsic (Camera Characteristics) & Extrinsic (e.g. Baseline)
Short Range ( < 5 meters), Structured IR Light Projection for RGB-D– Compare to ASUS Xtion and PrimeSense – Off-the-Shelf– Robust Depth Maps with Less Noise– Showing Significant Promise to Improve CV Scene Segmentation and Object
Recognition Compared to 2D– “Change Their Perception”, By Xiaofeng Ren, Dieter Fox, and Kurt Konolige,
IEEE RAS, December 2013.
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Noise in Passive Depth Maps
Robust Active Depth Map“Change Their Perception”, By Xiaofeng Ren, Dieter Fox, and Kurt Konolige, IEEE RAS, December 2013.
Design for Users with DisabilitiesMinority of Market, but Support Required
Visual ImpairmentHearing ImpairmentPhysical ImpairmentSpeech ImpairmentCognitive Impairments – Dyslexia, Autisim Sam Siewert 21
Cultural and Age ConsiderationsElderly, Age 50+ TabletChildren, Kids Tablet – e.g. IPAD Mini 2, Amazon Fire Kids Edition, etc.Language Localization – Fundamental Translation, Keyboard, Graphics for Native Language Support
Cultural Differences – E.g. Nodding or Shaking Head in Agreement
Global Marketplace – High Value Today with Globalization
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Cognitive Models - IntroductionChapter 11 of HCI - User Support Systems (Built-in Help)
Chapter 12 of HCI - Cognitive Models– Hierarchical Models – Task and Goal Structure
GOMS (Goals, Operators, Methods, Selection), p. 421-425Goal - what you want to achieveOperators - basic actionsMethods - splitting goal into many sub-goalsSelection - choice of method for more than one
– Linguistic Models – System Grammar
– Physical and Device Models – Human Motor Skills
– Cognitive Models – Combine All 3 of the Above
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