Computer Vision, Immersive Technology, and Digital Content

- Overview

Computer vision (CV) is a field of artificial intelligence (AI) that allows computers to interpret and understand visual information. It's used in many applications, including facial recognition, self-driving cars, and medical imaging. 

Immersive technology creates unique experiences by blending the physical world with digital or analog reality. Augmented reality (AR) and virtual reality (VR) are immersive technologies of two main types.

Immersive technology is a way to create digital experiences that are more interactive, engaging, and realistic than other online experiences. It aims to fully engage users by enveloping them in a simulated environment, such as an interactive simulation or virtual world. 

Digital content is any information that is created, stored, and distributed in a digital format. It can include text, images, audio, video, animations, interactive features, and more.

Some examples of immersive technology include: 

• Virtual reality (VR):
• Augmented reality (AR):
• Mixed reality (MR):
• Extended reality
• Projection mapping
• Immersive art installations

Some examples of immersive content include:

• Collaborative learning
• Virtual environments
• Group projects
• Team-building activities

Please refer to the following for more information:

• Wikipedia: Computer Vision
• Wikipedia: Immersion

The COVID-19 pandemic has accelerated the adoption of digital technologies at a faster speed than we could have imagined. As business undergoes change, companies are realizing the power of technology to unify dispersed, global talent. Virtual learning and telehealth are also becoming more advanced and could deliver benefits throughout the world.

Because new technologies are developing so quickly, it's difficult to predict exactly what the future internet will look like, but there's no doubt that the latest iteration of the web will transform nearly every part of our economy and society. 

As organizations look to take advantage of virtual worlds and the opportunities they present, they can explore these virtual worlds inside the studio, in the real world, and in the context of their businesses, providing a range of benefits that include: 

• Working alongside the designers and architects of virtual worlds, learning the new generation of creative tools, and simulation technologies that enable Unlimited Realities. 

• Creating hyper-realistic, physically-accurate digital twins that simulate natural environments, physical structures, industrial operations, transportation networks, including the humans and robots and AI agents working inside them, to accelerate design and planning cycles for all business paradigms. 

• Building shared virtual experiences that convene audiences for collaborative work, recreation, or education through AR/VR or mixed reality. 

• Exploring virtual world economies where transactions in digital currencies and assets will power an explosion of virtual services, experiences, and goods. 

• Enabling virtual world strategies that maximize positive impact on the planet, advancing client’s environment, social and corporate governance initiatives.

- Digital Content and Technologies

Our world has countless images and videos from the built-in cameras of our mobile devices alone. But while images can include photos and videos, it can also mean data from thermal or infrared sensors and other sources. Along with a tremendous amount of visual data (more than 3 billion images are shared online every day), the computing power required to analyze the data is now accessible and more affordable. 

This is a trivial problem for a human, even young children. We require at least the same capabilities from computers in order to unlock our images and videos.  

• A person can describe the content of a photograph they have seen once.
• A person can summarize a video that they have only seen once.
• A person can recognize a face that they have only seen once before. 

Sharing engaging and immersive visual content such as photos, videos, 360-degree and real-time augmented experiences is at the heart of staying connected and building community. 

Developing and refining advanced real-time computational photography and image understanding techniques that allow us to enhance our images and video, track and enhance faces, bodies and the 3D world, and capture and share the 3D world with high fidelity.

Research scientists and engineers span a myriad of disciplines including computer vision, computer graphics, computational photography, machine learning, interaction technologies and mobile development to unlock the commercial potential of virtual worlds.

[Meteora In Greece, Instagram]

- Computer Vision Technology

For many decades, people dreamed of creating machines with the characteristics of human intelligence, those that can think and act like humans. One of the most fascinating ideas was to give computers the ability to “see” and interpret the world around them. The fiction of yesterday has become the fact of today. 

Thanks to advancements in AI and computational power, computer vision (CV) technology has taken a huge leap toward integration in our daily lives.

CV is the field of computer science that focuses on creating digital systems that can process, analyze, and make sense of visual data (images or videos) in the same way that humans do. 

The concept of CV is based on teaching computers to process an image at a pixel level and understand it. Technically, machines attempt to retrieve visual information, handle it, and interpret results through special software algorithms. 

CV is an AI field that uses deep learning models and digital images to help machines understand and interpret the visual world. 

CV uses common tasks such as: 

• Image classification
• Object detection and localization
• Image segmentation

CV has many applications, including:

• Healthcare: CV can help automate tasks such as detecting cancerous moles in skin images or finding symptoms in x-ray and MRI scans. It can also detect neurological and musculoskeletal illnesses such as approaching strokes, balance issues, and gait issues.
• Manufacturing: CV can monitor manufacturing machinery for maintenance purposes and can also be used to monitor product quality and packaging on a production line.
• Self-driving cars: CV can help self-driving cars.
• Facial recognition: CV can be used in facial recognition technology, such as facial recognition software on smartphones that allow the owner's face to operate as a passcode.

Other applications of CV include: 

• Pedestrian detection
• Parking occupancy detection
• Traffic flow analysis
• Road condition monitoring
• X-Ray analysis
• CT and MRI
• Cancer detection
• Human pose tracking
• Interactive entertainment
• Augmented reality
• Robotics

- Computer Vision and AI

Computer vision (CV) is a branch of AI that helps computers understand and interpret visual data. CV uses machine learning models to identify and classify objects in digital images and videos. It also helps computers make decisions based on this data. 

CV simulates how humans see and understand their environment. It uses deep learning models and digital images from cameras and videos to accurately identify and classify objects. CV also uses neural networks to put all the parts of an image together and think on their own. 

CV is popular in manufacturing plants and is commonly used in AI-powered inspection systems.  

Some steps for training CV models include: 

• Start with an available data set
• Clean and organize the data set
• Build a model
• Train the model using the cleaned and organized data set
• Validate the model
• Deploy at scale

Some challenges with CV include: 

• Varied lighting conditions
• Perspective and scale variability
• Occlusion
• Lack of contextual understanding
• The need for more annotated data

- Computer Vision in Augmented and Virtual Reality

As technology advances, so does our ability to create immersive digital experiences. The birth of AR and VR technology is one of the most exciting advancements in recent years, with the potential to revolutionize the way we interact with digital content. 

The concept of CV is a field of study that, at its core, enables computers to "see" and understand the world around them, which is at the heart of these technologies. Therefore, CV in AR and VR is critical to creating engaging and immersive experiences that bridge the physical and digital worlds.

CV is used in augmented reality (AR) and virtual reality (VR) to: 

• Detect objects: CV can identify and detect real-world objects. This process is called object detection and is a key part of creating realistic AR experiences.
• Track movements: CV can track a user's movements, allowing the virtual content to respond to their position and gestures. This can make the AR and VR experience more engaging and intuitive.
• Recognize objects: CV can recognize and augment objects and spaces in real time.
• Decrypted images and videos: CV can decrypt images and videos for a variety of apps, such as character recognition.
• Build artificial environments: Augmented reality-enabled devices can build artificial environments that are combined with the physical environment.

- Spatial Computing

Spatial computing is a technology defined by computers blending data from the world around them in a natural way. Spatial computing in action could be as simple as controlling the lights when a person walks into a room or as complex as using a network of 3D cameras to model a factory process.

Components of spatial computing include: artificial intelligence, machine learning, haptic feedback, the Internet of Things (IoT), camera sensors, computer vision, etc.

The term "spatial computing" was coined by MIT Media Lab alumni Simon Greenwold in his 2003 thesis paper. The term originated in the field of GIS around 1985 or earlier to describe computations on large-scale geospatial information.

[More to come ...]