What is involved in Computer vision
Find out what the related areas are that Computer vision connects with, associates with, correlates with or affects, and which require thought, deliberation, analysis, review and discussion. This unique checklist stands out in a sense that it is not per-se designed to give answers, but to engage the reader and lay out a Computer vision thinking-frame.
How far is your company on its Computer vision journey?
Take this short survey to gauge your organization’s progress toward Computer vision leadership. Learn your strongest and weakest areas, and what you can do now to create a strategy that delivers results.
To address the criteria in this checklist for your organization, extensive selected resources are provided for sources of further research and information.
Start the Checklist
Below you will find a quick checklist designed to help you think about which Computer vision related domains to cover and 128 essential critical questions to check off in that domain.
The following domains are covered:
Computer vision, Motion capture, Projective geometry, VR photography, Structured-light 3D scanner, HTC Vive, Ridge detection, Olivier Faugeras, Driverless car, Samsung Gear VR, Machine vision, BMVA Summer School, Razer Hydra, Polyhedron model, Wired glove, Leap Motion, Synthetic aperture sonar, Optical flow, Light field, Object recognition, Cave automatic virtual environment, Virtual reality headset, Mobile robot, Head-mounted display, TreadPort Active Wind Tunnel, Hyperspectral imager, Camera resectioning, Visual hull, Head-up display, Computer stereo vision, Computer graphics, Haptic suit, Visual perception, Optical character recognition, Computer-human interaction, Free viewpoint television, Computer vision, Autonomous vehicle, Deep learning, Digital image, Google Goggles, Corner detection, PlayStation VR, Virtual reality, Projection augmented model, Image-based modeling and rendering, Solid-state physics, 3D reconstruction from multiple images, Augmented reality, Vision science, QR code, Image segmentation, Electromagnetic radiation, Artificial intelligence, Nikos Paragios, Human visual system, Simultaneous localization and mapping, Reality–virtuality continuum, Immersive technology, Side-scan sonar, Multimodal interaction, Quantum physics:
Computer vision Critical Criteria:
Learn from Computer vision tactics and diversify disclosure of information – dealing with confidential Computer vision information.
– What are our best practices for minimizing Computer vision project risk, while demonstrating incremental value and quick wins throughout the Computer vision project lifecycle?
– Marketing budgets are tighter, consumers are more skeptical, and social media has changed forever the way we talk about Computer vision. How do we gain traction?
– How do senior leaders actions reflect a commitment to the organizations Computer vision values?
Motion capture Critical Criteria:
Pay attention to Motion capture governance and document what potential Motion capture megatrends could make our business model obsolete.
– What are your current levels and trends in key measures or indicators of Computer vision product and process performance that are important to and directly serve your customers? how do these results compare with the performance of your competitors and other organizations with similar offerings?
– Risk factors: what are the characteristics of Computer vision that make it risky?
– Is there any existing Computer vision governance structure?
Projective geometry Critical Criteria:
Explore Projective geometry governance and budget for Projective geometry challenges.
– What are your key performance measures or indicators and in-process measures for the control and improvement of your Computer vision processes?
– What is the purpose of Computer vision in relation to the mission?
– What are the barriers to increased Computer vision production?
VR photography Critical Criteria:
Read up on VR photography decisions and correct better engagement with VR photography results.
– How do your measurements capture actionable Computer vision information for use in exceeding your customers expectations and securing your customers engagement?
– Do you monitor the effectiveness of your Computer vision activities?
– What are the long-term Computer vision goals?
Structured-light 3D scanner Critical Criteria:
Experiment with Structured-light 3D scanner adoptions and point out Structured-light 3D scanner tensions in leadership.
– Think about the functions involved in your Computer vision project. what processes flow from these functions?
– Are accountability and ownership for Computer vision clearly defined?
– What about Computer vision Analysis of results?
HTC Vive Critical Criteria:
Scan HTC Vive engagements and research ways can we become the HTC Vive company that would put us out of business.
– Does the Computer vision task fit the clients priorities?
– How do we go about Comparing Computer vision approaches/solutions?
– What are the business goals Computer vision is aiming to achieve?
Ridge detection Critical Criteria:
Interpolate Ridge detection quality and don’t overlook the obvious.
– What tools do you use once you have decided on a Computer vision strategy and more importantly how do you choose?
– How will you know that the Computer vision project has been successful?
– Who sets the Computer vision standards?
Olivier Faugeras Critical Criteria:
Refer to Olivier Faugeras goals and prioritize challenges of Olivier Faugeras.
– What are your most important goals for the strategic Computer vision objectives?
– Who will provide the final approval of Computer vision deliverables?
Driverless car Critical Criteria:
Confer over Driverless car results and secure Driverless car creativity.
– What will drive Computer vision change?
Samsung Gear VR Critical Criteria:
Confer re Samsung Gear VR management and drive action.
– Do those selected for the Computer vision team have a good general understanding of what Computer vision is all about?
– Why are Computer vision skills important?
Machine vision Critical Criteria:
Do a round table on Machine vision visions and research ways can we become the Machine vision company that would put us out of business.
– Are there any easy-to-implement alternatives to Computer vision? Sometimes other solutions are available that do not require the cost implications of a full-blown project?
– How is the value delivered by Computer vision being measured?
– What threat is Computer vision addressing?
BMVA Summer School Critical Criteria:
Deliberate over BMVA Summer School tasks and ask questions.
– What other jobs or tasks affect the performance of the steps in the Computer vision process?
– Does our organization need more Computer vision education?
Razer Hydra Critical Criteria:
Have a session on Razer Hydra tactics and prioritize challenges of Razer Hydra.
– Are we making progress? and are we making progress as Computer vision leaders?
– Can we do Computer vision without complex (expensive) analysis?
Polyhedron model Critical Criteria:
Value Polyhedron model strategies and look in other fields.
– In what ways are Computer vision vendors and us interacting to ensure safe and effective use?
– How can skill-level changes improve Computer vision?
Wired glove Critical Criteria:
Study Wired glove strategies and track iterative Wired glove results.
– Who is responsible for ensuring appropriate resources (time, people and money) are allocated to Computer vision?
– To what extent does management recognize Computer vision as a tool to increase the results?
Leap Motion Critical Criteria:
Have a meeting on Leap Motion planning and find the essential reading for Leap Motion researchers.
– What prevents me from making the changes I know will make me a more effective Computer vision leader?
– Have the types of risks that may impact Computer vision been identified and analyzed?
– How will you measure your Computer vision effectiveness?
Synthetic aperture sonar Critical Criteria:
Revitalize Synthetic aperture sonar governance and find the essential reading for Synthetic aperture sonar researchers.
– Which customers cant participate in our Computer vision domain because they lack skills, wealth, or convenient access to existing solutions?
– Are assumptions made in Computer vision stated explicitly?
– How do we Lead with Computer vision in Mind?
Optical flow Critical Criteria:
Merge Optical flow leadership and reduce Optical flow costs.
– Does Computer vision analysis show the relationships among important Computer vision factors?
– Why is it important to have senior management support for a Computer vision project?
Light field Critical Criteria:
Discourse Light field visions and pay attention to the small things.
– what is the best design framework for Computer vision organization now that, in a post industrial-age if the top-down, command and control model is no longer relevant?
– Why is Computer vision important for you now?
Object recognition Critical Criteria:
Group Object recognition engagements and reduce Object recognition costs.
– When a Computer vision manager recognizes a problem, what options are available?
– How can we improve Computer vision?
Cave automatic virtual environment Critical Criteria:
Transcribe Cave automatic virtual environment projects and check on ways to get started with Cave automatic virtual environment.
– How can the value of Computer vision be defined?
Virtual reality headset Critical Criteria:
Guard Virtual reality headset management and clarify ways to gain access to competitive Virtual reality headset services.
– Is Computer vision Required?
Mobile robot Critical Criteria:
Own Mobile robot engagements and pioneer acquisition of Mobile robot systems.
– What role does communication play in the success or failure of a Computer vision project?
– How will we insure seamless interoperability of Computer vision moving forward?
Head-mounted display Critical Criteria:
Examine Head-mounted display decisions and summarize a clear Head-mounted display focus.
– Consider your own Computer vision project. what types of organizational problems do you think might be causing or affecting your problem, based on the work done so far?
– How can you negotiate Computer vision successfully with a stubborn boss, an irate client, or a deceitful coworker?
– Do the Computer vision decisions we make today help people and the planet tomorrow?
TreadPort Active Wind Tunnel Critical Criteria:
Reconstruct TreadPort Active Wind Tunnel decisions and catalog TreadPort Active Wind Tunnel activities.
– Is maximizing Computer vision protection the same as minimizing Computer vision loss?
– Are there Computer vision Models?
Hyperspectral imager Critical Criteria:
Think about Hyperspectral imager goals and differentiate in coordinating Hyperspectral imager.
– Who are the people involved in developing and implementing Computer vision?
– What are internal and external Computer vision relations?
Camera resectioning Critical Criteria:
Differentiate Camera resectioning adoptions and look for lots of ideas.
– Why should we adopt a Computer vision framework?
Visual hull Critical Criteria:
Examine Visual hull tactics and frame using storytelling to create more compelling Visual hull projects.
– What are your results for key measures or indicators of the accomplishment of your Computer vision strategy and action plans, including building and strengthening core competencies?
– Are there Computer vision problems defined?
– How much does Computer vision help?
Head-up display Critical Criteria:
Frame Head-up display issues and find answers.
– For your Computer vision project, identify and describe the business environment. is there more than one layer to the business environment?
– What may be the consequences for the performance of an organization if all stakeholders are not consulted regarding Computer vision?
– What are our Computer vision Processes?
Computer stereo vision Critical Criteria:
Illustrate Computer stereo vision planning and reduce Computer stereo vision costs.
– What are specific Computer vision Rules to follow?
Computer graphics Critical Criteria:
Experiment with Computer graphics failures and assess what counts with Computer graphics that we are not counting.
– What other organizational variables, such as reward systems or communication systems, affect the performance of this Computer vision process?
– What are the Key enablers to make this Computer vision move?
Haptic suit Critical Criteria:
Brainstorm over Haptic suit decisions and assess what counts with Haptic suit that we are not counting.
– How do you incorporate cycle time, productivity, cost control, and other efficiency and effectiveness factors into these Computer vision processes?
– What is the source of the strategies for Computer vision strengthening and reform?
– Is Supporting Computer vision documentation required?
Visual perception Critical Criteria:
Explore Visual perception visions and prioritize challenges of Visual perception.
– What is the total cost related to deploying Computer vision, including any consulting or professional services?
– Is Computer vision Realistic, or are you setting yourself up for failure?
Optical character recognition Critical Criteria:
Brainstorm over Optical character recognition management and get going.
– What will be the consequences to the business (financial, reputation etc) if Computer vision does not go ahead or fails to deliver the objectives?
Computer-human interaction Critical Criteria:
Infer Computer-human interaction engagements and look at the big picture.
– Among the Computer vision product and service cost to be estimated, which is considered hardest to estimate?
– Do Computer vision rules make a reasonable demand on a users capabilities?
Free viewpoint television Critical Criteria:
Focus on Free viewpoint television failures and cater for concise Free viewpoint television education.
– How likely is the current Computer vision plan to come in on schedule or on budget?
Computer vision Critical Criteria:
Air ideas re Computer vision management and gather practices for scaling Computer vision.
– What potential environmental factors impact the Computer vision effort?
Autonomous vehicle Critical Criteria:
Dissect Autonomous vehicle management and report on developing an effective Autonomous vehicle strategy.
– How do you determine the key elements that affect Computer vision workforce satisfaction? how are these elements determined for different workforce groups and segments?
Deep learning Critical Criteria:
Rank Deep learning decisions and don’t overlook the obvious.
– Is the scope of Computer vision defined?
Digital image Critical Criteria:
Understand Digital image visions and describe the risks of Digital image sustainability.
– Meeting the challenge: are missed Computer vision opportunities costing us money?
Google Goggles Critical Criteria:
Incorporate Google Goggles adoptions and overcome Google Goggles skills and management ineffectiveness.
– In the case of a Computer vision project, the criteria for the audit derive from implementation objectives. an audit of a Computer vision project involves assessing whether the recommendations outlined for implementation have been met. in other words, can we track that any Computer vision project is implemented as planned, and is it working?
Corner detection Critical Criteria:
Weigh in on Corner detection strategies and acquire concise Corner detection education.
– Who will be responsible for documenting the Computer vision requirements in detail?
– How do we maintain Computer visions Integrity?
PlayStation VR Critical Criteria:
Differentiate PlayStation VR tactics and plan concise PlayStation VR education.
– Who will be responsible for making the decisions to include or exclude requested changes once Computer vision is underway?
– Does Computer vision analysis isolate the fundamental causes of problems?
Virtual reality Critical Criteria:
Substantiate Virtual reality governance and gather Virtual reality models .
– What are the Essentials of Internal Computer vision Management?
– Do we all define Computer vision in the same way?
Projection augmented model Critical Criteria:
Categorize Projection augmented model failures and create Projection augmented model explanations for all managers.
– Who will be responsible for deciding whether Computer vision goes ahead or not after the initial investigations?
– Which individuals, teams or departments will be involved in Computer vision?
– What business benefits will Computer vision goals deliver if achieved?
Image-based modeling and rendering Critical Criteria:
Survey Image-based modeling and rendering decisions and change contexts.
– A compounding model resolution with available relevant data can often provide insight towards a solution methodology; which Computer vision models, tools and techniques are necessary?
Solid-state physics Critical Criteria:
Brainstorm over Solid-state physics adoptions and know what your objective is.
– Will new equipment/products be required to facilitate Computer vision delivery for example is new software needed?
3D reconstruction from multiple images Critical Criteria:
Deliberate 3D reconstruction from multiple images adoptions and simulate teachings and consultations on quality process improvement of 3D reconstruction from multiple images.
Augmented reality Critical Criteria:
Co-operate on Augmented reality tactics and prioritize challenges of Augmented reality.
– What new services of functionality will be implemented next with Computer vision ?
Vision science Critical Criteria:
Shape Vision science outcomes and probe the present value of growth of Vision science.
– Think about the people you identified for your Computer vision project and the project responsibilities you would assign to them. what kind of training do you think they would need to perform these responsibilities effectively?
QR code Critical Criteria:
Use past QR code planning and drive action.
Image segmentation Critical Criteria:
Shape Image segmentation strategies and achieve a single Image segmentation view and bringing data together.
Electromagnetic radiation Critical Criteria:
Deliberate over Electromagnetic radiation results and question.
– What are the disruptive Computer vision technologies that enable our organization to radically change our business processes?
Artificial intelligence Critical Criteria:
Scan Artificial intelligence leadership and define what our big hairy audacious Artificial intelligence goal is.
– Will Computer vision have an impact on current business continuity, disaster recovery processes and/or infrastructure?
Nikos Paragios Critical Criteria:
Discuss Nikos Paragios tasks and raise human resource and employment practices for Nikos Paragios.
– What are the key elements of your Computer vision performance improvement system, including your evaluation, organizational learning, and innovation processes?
Human visual system Critical Criteria:
Start Human visual system planning and define what do we need to start doing with Human visual system.
Simultaneous localization and mapping Critical Criteria:
Chart Simultaneous localization and mapping projects and proactively manage Simultaneous localization and mapping risks.
– What are the success criteria that will indicate that Computer vision objectives have been met and the benefits delivered?
Reality–virtuality continuum Critical Criteria:
Focus on Reality–virtuality continuum outcomes and adopt an insight outlook.
– How do we ensure that implementations of Computer vision products are done in a way that ensures safety?
– Which Computer vision goals are the most important?
Immersive technology Critical Criteria:
Sort Immersive technology management and revise understanding of Immersive technology architectures.
– How do we manage Computer vision Knowledge Management (KM)?
Side-scan sonar Critical Criteria:
Contribute to Side-scan sonar planning and catalog Side-scan sonar activities.
Multimodal interaction Critical Criteria:
Apply Multimodal interaction management and reduce Multimodal interaction costs.
Quantum physics Critical Criteria:
Set goals for Quantum physics outcomes and reduce Quantum physics costs.
– Is the Computer vision organization completing tasks effectively and efficiently?
– Do we have past Computer vision Successes?
This quick readiness checklist is a selected resource to help you move forward. Learn more about how to achieve comprehensive insights with the Computer vision Self Assessment:
Author: Gerard Blokdijk
CEO at The Art of Service | http://theartofservice.com
Gerard is the CEO at The Art of Service. He has been providing information technology insights, talks, tools and products to organizations in a wide range of industries for over 25 years. Gerard is a widely recognized and respected information expert. Gerard founded The Art of Service consulting business in 2000. Gerard has authored numerous published books to date.
To address the criteria in this checklist, these selected resources are provided for sources of further research and information:
Computer vision External links:
Focal Systems – Deep Learning and Computer Vision …
Computer Vision Syndrome and Digital Eye Strain
Sighthound – Industry Leading Computer Vision
Motion capture External links:
Animation Software – Markerless Motion Capture – …
OptiTrack – Motion Capture Systems
Shadow Motion Capture System
Projective geometry External links:
Projective geometry | Britannica.com
Projective Geometry | Definition of Projective Geometry …
The axioms of projective geometry – Internet Archive
VR photography External links:
VR Photography – Home | Facebook
NadirPatch.com VR photography tools
Structured-light 3D scanner External links:
Structured-light 3D Scanner Market – Global Trends, …
HTC Vive External links:
HTC Vive Installation Guide – Steam
HTC Vive PRE Installation Guide – SteamVR – Steam Support
Get the HTC VIVE Virtual Reality System at Microsoft Store and compare products with the latest customer reviews and ratings. Download or ship for free. Free returns.
Ridge detection External links:
math – Implementing ridge detection – Stack Overflow
Ridge Detection – ImageJ
A demo for image segmentation using iterative watersheding plus ridge detection.
Olivier Faugeras External links:
Olivier Faugeras | Facebook
Olivier Faugeras – The Mathematics Genealogy Project
Olivier Faugeras | Flickr
Driverless car External links:
What is driverless car? – Definition from WhatIs.com
Samsung Gear VR External links:
Samsung Gear VR – Virtual Reality | Samsung US
Mobile virtual reality is finally here with the Samsung Gear VR, powered by select Samsung phones. Free shipping available. Get it from Verizon.
Amazon.com: Samsung Gear VR w/Controller (2017) – Latest Edition – Note 8, GS8s, GS7s, Note 5, GS6s (US Version w/ Warranty): Cell Phones & Accessories
Machine vision External links:
King Barcode | Barcode & Machine Vision Systems
BMVA Summer School External links:
BMVA Summer School (@BmvaCvss) | Twitter
BMVA Summer School – Stuart James
Razer Hydra External links:
Amazon.com: Razer Hydra PC Gaming Motion Sensing Controllers (RZ06-00630100-R3U1): Computers & Accessories
Razer Hydra brings motion control to PC gamers – New Atlas
Razer Hydra review – Engadget
Polyhedron model External links:
Animated Polyhedron Models – Math Is Fun
Polyhedron Models – Free Picture Puzzle – All-Star Puzzles
Wired glove External links:
Wired glove – Revolvy
Wired glove – Infogalactic: the planetary knowledge core
Leap Motion External links:
Setup Guide — Leap Motion
Leap Motion Gallery – Demos and experiments from the …
Unity — Leap Motion Developer
Synthetic aperture sonar External links:
Synthetic aperture sonar – Revolvy
https://www.revolvy.com/topic/Synthetic aperture sonar
[PDF]Synthetic Aperture Sonar System – AUVAC.org
Synthetic Aperture Sonar. (eBook, 1971) [WorldCat.org]
Optical flow External links:
Optical Flow – Centeye
PMW3901 Optical Flow Sensor from onehorse on Tindie
Light field External links:
Amazon.com : Lytro Light Field Camera, 8GB, Graphite : Point And Shoot Digital Cameras : Amazon Launchpad
Object recognition External links:
Object Recognition – MATLAB & Simulink – MathWorks
Visual object recognition (eBook, 2011) [WorldCat.org]
Cave automatic virtual environment External links:
CAVE System | CAVE Automatic Virtual Environment
[PDF], THE CAVE AUTOMATIC VIRTUAL ENVIRONMENT: …
Virtual reality headset External links:
FreeflyVR is a Virtual Reality headset for mobile phones
Virtual reality headset – Oculus VR, LLC
Mobile robot External links:
Mobile Robot – LearnOBots
The URANUS Mobile Robot – The Robotics Institute …
Head-mounted display External links:
I-Port Near-Eye and Head-Mounted Display Systems – Intevac
TreadPort Active Wind Tunnel External links:
TreadPort Active Wind Tunnel – Revolvy
https://www.revolvy.com/topic/TreadPort Active Wind Tunnel
Treadport Active Wind Tunnel – School of Computing
Hyperspectral imager External links:
OCI™-2000 Snapshot Handheld Hyperspectral Imager – …
UAV Hyperspectral Imager SOC710-GX – Surface Optics …
Camera resectioning External links:
Camera resectioning – definition of Camera resectioning …
Visual hull External links:
Visual Hull – Home | Facebook
Visual Hull Matlab – File Exchange – MATLAB Central
Head-up display External links:
HUD (Head-Up Display) | Garmin
The Best Head-Up Display For Your Car | Navdy
HUDWAY Cast — The 1st Head-Up Display Allows Using …
Computer stereo vision External links:
Patent WO1997018523A3 – Computer stereo vision …
Computer graphics External links:
Computer Graphics : Dallas County Community College District
Computer Graphics Quiz 1 Flashcards | Quizlet
3D computer graphics – ScienceDaily
Haptic suit External links:
Teslasuit – full-body haptic suit of Virtual Reality – YouTube
Visual perception External links:
Visual perception (Book, 1973) [WorldCat.org]
Visual Perception (eVideo, 2015) [WorldCat.org]
VISUAL PERCEPTION – Psychology Dictionary
Computer-human interaction External links:
HICHI: Hawaii Computer-Human Interaction Lab | …
Free viewpoint television External links:
Overview of free viewpoint television – ScienceDirect
VIEW SYNTHESIS IN FREE VIEWPOINT TELEVISION (FTV) AND …
Free viewpoint television – STANFORD TALKS
Computer vision External links:
Focal Systems – Deep Learning and Computer Vision …
Computer Vision Syndrome and Digital Eye Strain
Sighthound – Industry Leading Computer Vision
Deep learning External links:
Focal Systems – Deep Learning and Computer Vision …
MIT 6.S094: Deep Learning for Self-Driving Cars
Digital image External links:
Standard Web Digital Image Sizes – Tim Stanley
American Lock® Digital Image Library
Digital Image File Types Explained – WFU
Google Goggles External links:
Google Goggles – WIRED
Google Goggles vs. itself on iPhone, Android – CNET
Google Goggles – App Review – Common Sense Media
Corner detection External links:
Edge and Corner Detection – YouTube
Fast corner detection – ScienceDirect
matlab – Harris Corner Detection – Stack Overflow
PlayStation VR External links:
PlayStation VR – Over 100 games and counting. Feel them all.
PlayStation VR (PS VR) – reddit
Virtual reality External links:
3D Camera | 3D scanning | Virtual Reality – Matterport
NASA Uses Students To Develop Virtual Reality Programs : NPR
The Virtual Reality Tour of the State Capitol Building
Image-based modeling and rendering External links:
Image-Based Modeling and Rendering
[PDF]Image-based Modeling and Rendering of Surfaces …
3D reconstruction from multiple images External links:
3D Reconstruction from multiple images by padmapriya …
[PDF]3D Reconstruction from Multiple Images – MIT
http://web.mit.edu/smart/research/biosym/15 June 2015 shakil.pdf
[PDF]3D Reconstruction from Multiple Images Using …
Augmented reality External links:
Augmented Reality – Mashable
Vision science External links:
vision science studios – Just another WordPress site
UAB – Vision Science Research Center – Home
Dennis M. Levi « Vision Science at UC Berkeley
QR code External links:
Create QR Code
The QR Code Generator – Official Site
Mar 16, 2016 · HOW THE APP WORKS To scan a QR code or barcode simply open the app, point the camera at the code, and you’re done! There is no need to take a …
Image segmentation External links:
matlab – Image Segmentation Using K means – Stack Overflow
http://In computer vision, image segmentation is the process of partitioning a digital image into multiple segments (sets of pixels, also known as superpixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze.
Image segmentation – Mathematics Is A Science
Electromagnetic radiation External links:
Electromagnetic radiation | physics | Britannica.com
Title: Electromagnetic Radiation’s Role in the Story
Electromagnetic radiation – Biology-Online Dictionary
Artificial intelligence External links:
Artificial Intelligence for B2B Sales | Collective[i]
Human visual system External links:
Human Visual System Flashcards | Quizlet
[PDF]HUMAN VISUAL SYSTEM—IMAGE FORMATION 539
[PDF]Human Visual System – Washington State
Simultaneous localization and mapping External links:
[PDF]Simultaneous Localization and Mapping
Simultaneous Localization and Mapping | MARINE …
Immersive technology External links:
ITA3D – The Immersive Technology Alliance
YouVisit: Immersive Technology Event Series (New …
What is Immersive Technology? – Immersive Authority
Multimodal interaction External links:
Description: Multimodal Interaction with W3C Standards
Multimodal Interaction in Architectural Design Applications
Quantum physics External links:
SparkNotes: SAT Physics: Quantum Physics
The Quantum Physics of Free Will – Scientific American