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Application of 3D Sensing Technology in Era of AIOT

  • Report

  • 31 Pages
  • June 2018
  • Region: Global
  • Market Intelligence & Consulting Institute (MIC)
  • ID: 4580929

3D sensing technology mimics the human-visual system using optical technology, which allows products integrated with AI (Artificial Intelligence) and IoT (Internet of Things) technologies to have 3D computer vision. Besides improving facial recognition accuracy and human-machine interaction via hand movements, 3D sensing technology also speeds up the pace of Level 5 autonomous vehicle developments. With this technology, industrial robots can perform complicated tasks such as 3D picking or product quality inspection. This report looks into 3D sensing technology and its potential applications in the next generation of IoT (Internet of Things).

List of Topics

  • Development of 3D sensing technology, touching on its definition and key technologies
  • Applications of 3D sensing for use in four areas such as facial recognition, gesture control, smart vehicles, and industrial robots with examples given

Table of Contents

1. Development of 3D Sensing Technology
1.1 Definition of 3D Sensing
1.2 Key 3D Sensing Technologies
1.1.1 Structured Light
1.1.2 TOF (Time of Flight)
1.1.3 Stereo Vision

2. Applications of 3D Sensing
2.1 Application #1: Facial Recognition
2.1.1 Bezel-less Smartphone Trend Drives 3D Facial Recognition Development
2.1.2 Structured Light Technology Suitable for 3D Facial Recognition with Fast, Accurate, and Excellent Short-range Measurement
2.1.3 3D Facial Recognition-enabled Smartphones to Accelerate Mobile Financial Service Applications
2.2 Application #2: Gesture Control
2.2.1 AR/VR with Intuitive Gesture Control Enhances Immersive Experience
2.2.2 Google Creates 3D Gesture Control Ecosystem with Project Soli
2.3 Application #3: Smart Vehicles
2.3.1 3D Environment Sensing as First Step to Autonomous Security and Driving for Smart Vehicles
2.3.2 ADAS Regulations to Boost Camera and Radar Demand; Solid-static LiDar Market to Thrive
2.3.3 Vehicle Camera as Standards Equipment
2.3.4 Long-range 77GHz mmWave Radar as Focal Development
2.3.5 LiDAR towards Mass Production, Accelerating Realization of L3 Autonomy
2.4 Application #4: Industrial Robots
2.4.1 Robotic Arms with 3D Computer Vision Enable Randomly Picking of Parts and Quality Check
2.4.2 Mobile Robotic Arms with 3D Sensing Optimizes Human-machine Collaboration and Near-field Navigation

3. Conclusion
3.1 3D Sensing Technology Endows AI + IoT Products with Vision, Smarting Up Human-Machine Collaboration
3.2 UI with 3D Facial Recognition Enhances User Experience and Drives Innovative Fintech Services
3.3 Gesture Control Enables Intuitive Human-Machine Interaction and More Immersive VR Experience
3.4 Demand for Solid-state LiDAR to Rise
3.5 Industrial Robots with 3D Computer Vision Make Unmanned Factories a Reality

AppendixGlossary of TermsList of Companies
List of Tables
Table 1 Pros and Cons of Key 3D Sensing Technologies
Table 2 Application of 3D Sensors in ADAS
Table 3 Comparison of MMIC Process Technologies
Table 4 Types of LiDAR Systems

List of Figures
Figure 1 3D Image Created by LiDAR in Smart Vehicle
Figure 2 Three Key 3D Sensing Technologies
Figure 3 Applications of 3D Sensing Technology at CES 2018
Figure 4 Evolution of Identification Technology in Smartphones
Figure 5 Facial Recognition Process of Apple’s Face ID
Figure 6 Online Banking Services Using Facial Recognition
Figure 7 Evolution of AR/VR HMI
Figure 8 Applications of Gesture Control using Google’s Project Soli
Figure 9 Autonomous Driving Levels
Figure 10 3D Sensors of Smart Vehicles
Figure 11 Automated Production Lines with 3D Sensing



Companies Mentioned

A selection of companies mentioned in this report includes:

  • Amazon
  • Apple
  • Continental
  • Google
  • Infineon
  • Innoluce
  • Intel RealSense
  • Leap Motion
  • Microsoft
  • Nintendo
  • NXP
  • Oppo
  • Pingan
  • PrimeSense
  • Quanergy
  • Samsung
  • Sensory
  • Sony
  • STMicro
  • Tenzr
  • TI
  • uSens
  • Velodyne
  • WeBank
  • Xiaom


Primary research with a holistic, cross-domain approach

The exhaustive primary research methods are central to the value that the analyst delivers. A combination of questionnaires and on-site visits to the major manufacturers provides a first view of the latest data and trends. Information is subsequently validated by interviews with the manufacturers' suppliers and customers, covering a holistic industry value chain. This process is backed up by a cross-domain team-based approach, creating an interlaced network across numerous interrelated components and system-level devices to ensure statistical integrity and provide in-depth insight.

Complementing primary research is a running database and secondary research of industry and market information. Dedicated research into the macro-environmental trends shaping the ICT industry also allows the analyst to forecast future development trends and generate foresight perspectives. With more than 20 years of experience and endeavors in research, the methods and methodologies include:


  • Component supplier interviews
  • System supplier interviews
  • User interviews
  • Channel interviews
  • IPO interviews
  • Focus groups
  • Consumer surveys
  • Production databases
  • Financial data
  • Custom databases


  • Technology forecasting and assessment
  • Product assessment and selection
  • Product life cycles
  • Added value analysis
  • Market trends
  • Scenario analysis
  • Competitor analysis