Hardware Podcasts

161: Magenta Doesn't Exist

Embedded.fm · 19 Jul 2016 · 1h 11m

What this episode covers

Kat Scott, a senior software engineer at Planet and co-author of 'Practical Computer Vision with SimpleCV', explains the fundamentals of computer vision, emphasizing that it is largely about discarding irrelevant data to find specific signals. She details the challenges of industrial computer vision, noting that consistent lighting and constrained environments are critical for success, and warns that achieving high accuracy in machine learning requires exponentially more data for each decimal place of improvement. Scott also discusses the technical pipeline behind real-time face filters like those on Snapchat, which involve face detection, 3D mesh fitting, and reprojection, and advises engineers to use tools like OpenCV and ROS rather than reinventing the wheel.

Most relevant to

large enterprises

Topics

Mentioned

Companies
Planet
Products
Snapchat, Raspberry Pi
Tools
SimpleCV, OpenCV, ROS, Jupyter, Emacs, Matplotlib, NumPy, FFmpeg, VLFeat

Related episodes from other shows

Other shows on the same ground, closest first.

  • EE Times Current · 37m

    Machine Vision: Seeing is Believing

    Jeff Bier, president of BDTI and founder of the Edge AI and Vision Alliance, discusses the evolution of machine vision from constrained manufacturing environments to complex natural settings. He explains how the industry shifted from handcrafted algorithms to data-driven deep learning, enabling applications like mask detection and elder care monitoring. Bier also highlights the necessity of sensor fusion, such as combining vision with radar or LiDAR, to overcome environmental limitations like fog or darkness.

    AI & machine learningSensors & measurement in products
    7 chapters

  • The Next Byte Podcast · 26m

    44. How Computer Vision Is Changing Your World

    Hosts Daniel and Farbod discuss how computer vision AI is applied in manufacturing and agriculture, featuring insights from Plain Sight AI and a project by the Technical University of Denmark. They explain Plain Sight AI's three levels of vision systems for detecting hazardous objects on production lines, emphasizing that Level 3 instance segmentation offers superior sorting and counting capabilities. The hosts also detail a robot developed by PhD student Ronja Goldring to autonomously remove weeds from organic dairy farms using laser or electrocution, highlighting the importance of large, diverse training datasets and collaboration with end-users.

    AI & machine learningIndustrial & consumer product design
    5 chapters

  • The Next Byte Podcast · 18m

    221. Generational Discovery & The New Age of Computer Vision

    The hosts discuss research from Princeton University and the University of Washington, led by a professor and his PhD student, on using metasurfaces to revolutionize computer vision. They explain how these nanostructured, flat lenses pre-filter light to perform hardware-level edge detection, achieving a 99% reduction in computational power compared to traditional software-based methods. The technology, which can be as small as a grain of salt, beats industry benchmarks like AlexNet and enables faster, more efficient object detection for applications like autonomous vehicles and smart home devices.

    Mechanical engineeringAI & machine learning
    7 chapters

  • IoT For All Podcast · 30m

    Automation through Computer Vision and AI | ZenduIT's Vishal Singh

    Vishal Singh, Founder and CTO of ZenduIT, discusses the evolution of IoT from simple GPS tracking to complex computer vision and AI solutions for fleet management and airport operations. He explains how ZenduIT uses edge computing to detect driver fatigue and phone usage, emphasizing the critical role of high-quality data and proper camera positioning in building reliable AI models. Singh also addresses the challenges of AI accuracy, the security risks of connected cameras, and the future trend of managed services for video analytics.

    AI & machine learningEmbedded firmware
    7 chapters

  • OnTrack · 47m

    AI Vision Systems in Manufacturing with Deepview's Eliyahu Davis

    Eliyahu Davis, lead engineer at Deepview AI, explains how his company uses deep learning to automate factory inspection, reducing setup time from 40 hours to minutes. Davis details his transition from aerospace software engineering to hardware, describing how he learned Altium Designer through online resources and mentorship to design the camera's PCB. He discusses the technical challenges of running neural network training on edge devices and the future of foundation models in industrial automation.

    Embedded firmwareEDA & CAD tools
    7 chapters

The summary, chapters and topics are generated from the episode’s audio by this directory, not written by Embedded.fm. The episode itself belongs to its publisher.