Oak-D Cameras and OpenCV

Welcome, readers! Today, we’re diving into the fascinating world of Oak-D cameras. Have you ever wondered what these devices are, how they work, or why they’re creating such a buzz in the tech world? If so, you’ve come to the right place. We’re going to explore the ins and outs of Oak-D cameras, break down their complex workings into understandable chunks, and showcase some visual examples to bring the technology to life. So, let’s get started!

Oak-D Cameras

Luxonis developed Oak-D cameras. They are a unique blend of standard and depth cameras, backed by an onboard AI chip. This combination enables these devices to perceive depth and spatial information, much like our own eyes. The ‘D’ in Oak-D stands for depth, indicating their ability to capture 3D depth information. This depth perception allows for the understanding of the distance of objects and even identify and track multiple objects in a scene, similar to how a Kinect or Zed camera would as well.

But the capabilities of Oak-D cameras extend beyond capturing depth information. Each camera comes equipped with an Intel Movidius Myriad X VPU, a powerful chip designed specifically for running AI tasks. This onboard AI capability allows the camera to process and understand the depth information in real-time, making Oak-D cameras a groundbreaking addition to the field of computer vision.

Computer Vision

As we explore these cameras, it’s important to understand the field they operate in: computer vision. This branch of artificial intelligence aims to teach computers to ‘see’ and interpret visual information from the world around us, much like humans do. The concept of computer vision has been around since the 1960s, but it’s only in recent years, with advancements in AI and machine learning, that we’ve seen significant progress.

Today, computer vision is a rapidly evolving field. State-of-the-art technology is capable of impressive feats, from recognizing faces in a crow, detecting objects for self-driving cars, and detecting people’s skeleton joints. It’s transforming the way machines interact with the world and is being used across various industries, including healthcare, retail, transportation, and security.

Stereo Vision

Stereo vision is a fascinating concept that allows us to perceive depth and distance. It’s a key part of how humans, and many animals, see the world in three dimensions. Now, the principle of stereo vision is quite simple and is based on the fact that our eyes are about two inches apart; this means that each eye sees the world from a slightly different angle. Our brain takes these two slightly different images and combines them, using the differences between them to judge distance and create a sense of depth. This is known as binocular disparity. Cool, huh?

In the context of technology and computer vision, stereo vision works in a similar way. Devices like Oak-D cameras use two cameras to capture the same scene from slightly different angles. The device then uses algorithms to compare these two images, calculate the differences, and create a depth map of the scene. This allows the device to understand how far away objects are and perceive the world in 3D, much like we do! This is similar to how a Zed camera works, as opposed to a Kinect which uses Time-of-flight techniques instead of having two cameras.

OpenCV

OpenCV, short for Open Source Computer Vision Library, is a massive toolbox filled with all sorts of handy tools for computer vision. Being open-source, it’s freely available for anyone to use and has been designed to accelerate the development of computer vision applications.

Think of OpenCV as a Swiss Army knife for computer vision. It has different ‘blades’ or modules, each designed for a specific task:

• Core Functionality (core): This is the main blade of the knife. It provides the basic building blocks and functions that all the other modules use.
• Image Processing (imgproc): A set of filters for a camera. It can change the colors in an image, smooth out rough edges, and much more.
• Video Analysis (video): A detective, analyzing videos to find patterns and track movements.
• Camera Calibration and 3D Reconstruction (calib3d): A pair of 3D glasses. It helps computers understand the depth and distance in images, making flat pictures look three-dimensional.
• 2D Features Framework (features2d): A treasure hunter, finding interesting points or ‘features’ in images.
• Object Detection (objdetect): A security guard, spotting specific objects like faces or cars in images.
• High-level GUI (highgui): The user manual, providing an easy way for people to interact with the program.
• Video I/O (videoio): A translator, helping the program understand different video formats.

Now, let’s see how this powerful toolbox can work together with Oak-D cameras to create amazing applications!

OpenCV and Oak-D

When you pair OpenCV with Oak-D cameras, you get a powerful duo that can tackle a wide range of computer vision tasks. Imagine OpenCV as the brain and Oak-D as the eyes. The Oak-D cameras capture detailed 3D images of the world, while OpenCV processes these images, making sense of what they represent.

For example, let’s say you’re building a robot that can navigate on its own. The Oak-D camera, with its depth perception, can capture 3D images of the robot’s surroundings. It can identify objects and their distances, creating a detailed map of the environment. This information is then passed on to OpenCV.

OpenCV, with its vast array of tools, can analyze this data. It can recognize objects, track their movement, and even predict their future positions. With this information, it can make decisions on where the robot should go next, avoiding obstacles and efficiently navigating its environment.

Applications

• Autonomous Vehicles: Identification of other vehicles, pedestrians, and obstacles. This can help autonomous vehicles navigate safely and efficiently.

• Smart Home Security: Face recognition and differentiation between residents and strangers, and alert homeowners of any unusual activity.

• Retail: Tracking of customer movement and identify which products they interact with, and even predict their shopping behavior.

• Healthcare: This technology is used for patient monitoring, fall detection, and even in surgery.

• Drones: Understanding the environment is key for navigation, especially in complex terrains. Oak-D cameras can provide detailed 3D images of the surroundings, and OpenCV can process this data to help the drone avoid obstacles and navigate efficiently.

Why is Oak-D worth our attention?

Here are 5 reasons why you should consider adding the Oak-D resources to your creative process:

• Availability

Unlike Kinect cameras, which can be hard to find, Oak-D cameras are readily available. You won’t have to scour the internet to get your hands on one.

• Community Support

The large OpenCV community is actively engaged with Oak-D. This means you have a wealth of resources and collaborative support at your disposal, unlike with Zed cameras where updates and new features are primarily company-driven.

• Efficiency

The onboard AI chip in Oak-D cameras offloads a significant amount of processing work. This means your computer can focus on other tasks, making your operations more efficient.

• Customization

The Oak-D range offers a variety of models to suit different needs. Whether you require night vision or long-distance runs, there’s a product model for you.

• Up-to-Date

Luxonis regularly releases new models to cater to evolving use cases and feature sets. This represents the opportunity to expand and challenge the setups you develop, ensuring creative evolution!

Oak-D and TouchDesigner

If you are interested in getting together Oak-D and TouchDesigner, Blake Marques Carrington has put together this 5-chapter introduction to this type of connectivity. Check it out!

Wrap Up

As you can see, there is a lot to explore in the world of Oak-D cameras, TouchDesigner, OpenCV and all the other wonderful components that are shaping the world of computer vision. If you haven’t delved into this world yet, don’t be intimidated. The resources available are vast and plentiful!

Focus on what goals you’d like to reach in terms of computer vision knowledge and start your journey. Godspeed!