Computer Vision – 5 Amazing Ways Of Using Computer Vision In Media And Entertainment
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Computer vision has revolutionized the media and entertainment industry, including visual media, TV and film production, interactive media, sports, games, advertising, and enhancing gamified customer experiences to perceive the world as humans do. Its impact can be seen in content moderation, scene detection, subtitle generation, and numerous other areas within the industry.
Engineers have utilized various technologies to train computers to visually perceive objects and people and identify and process images and videos. Notable technologies include image recognition and processing, pattern recognition, and many others. Machine learning (ML) and deep learning (DL) principles have made these advancements possible. These technologies form the foundation for developing computer vision systems and applications.
Engineers have utilized various technologies to train computers to visually perceive objects and people and identify and process images and videos. Notable technologies include image recognition and processing, pattern recognition, and many others. Machine learning (ML) and deep learning (DL) principles have made these advancements possible. These technologies form the foundation for developing computer vision systems and applications.
Machine learning (ML) has empowered computers to achieve a visual perception comparable to human eyesight. As a result, computer vision has found widespread applications across diverse industries.
the following are ways computer vision is used in media and entertainment
the following are ways computer vision is used in media and entertainment
1. Augmented Intelligence: AR, VR, MR
Computer vision enables augmented intelligence and elevates the gaming and customer experience.
Augmented intelligence encompasses augmented reality, virtual reality, and mixed reality. It represents a collaborative model where humans and AI work together, leading to enhanced performance, improved decision-making, and a guiding influence in accomplishing tasks.
As per Gartner’s Hype Cycle for AI in 2019, augmented intelligence emerges when companies integrate AI into various business workflows at a large scale. The advancement of immersive virtual reality environments and associated hardware has introduced new possibilities. Different ML-based “realities” forms enable users to interact with virtual objects in distinct ways.
As per Gartner’s Hype Cycle for AI in 2019, augmented intelligence emerges when companies integrate AI into various business workflows at a large scale. The advancement of immersive virtual reality environments and associated hardware has introduced new possibilities. Different ML-based “realities” forms enable users to interact with virtual objects in distinct ways.
Virtual Reality (VR)
VR technology allows users to immerse themselves in new realities, enhancing their surroundings with virtual artworks from extensive VR libraries or delving into thrilling gaming experiences. This cutting-edge VR experience can be achieved through devices like Oculus Rift, Samsung Gear VR, and HTC Vive. By entering the virtual world, users are separated from the sounds and voices of their physical surroundings, providing them with unlimited space for exploration and interaction.
Augmented Reality (AR)
Augmented reality (AR) technology enriches the real world with virtual images, objects, animations, visual effects, captions, and other elements. Examples of AR-driven applications include Pokémon GO, Snapchat, and Google Glass. This technology also enables the development of innovative solutions such as AR Mirror, which enhances customer experiences, and Smart Glasses, which were once solely seen in movies but are now a reality. AR technology has also done captivating sports like drone racing possible. We will explore these AR applications further in our article.
Mixed Reality (MR)
Mixed reality (MR) shares similarities with AR, but it goes further by creating virtual objects that seamlessly integrate into the user’s physical environment. With MR, virtual objects appear in the room, occupying specific positions. An example of MR technology is the Microsoft HoloLens, which enables users to see each other in a shared virtual environment through a head-mounted display (HMD).
2. Smart Glasses
The advancements in hardware capabilities and the significant progress in machine learning have authorised the development of AR headsets. Google recently introduced new cutting-edge smart glasses that leverage these technologies. These state-of-the-art devices are equipped with Qualcomm’s Snapdragon XR1 chip, specifically designed to enhance the capabilities of augmented intelligence.
Glass primarily caters to the needs of businesses, offering a solution that can enhance product quality, decrease time to market, and reduce costs in various industries. Microsoft HoloLens, a competitor product, focuses on mixed reality and is primarily designed for industrial applications.
This versatile solution extends beyond entertainment and finds utility in sectors such as automotive design, healthcare, military applications, and enhancing consumers’ in-store experiences.
This versatile solution extends beyond entertainment and finds utility in sectors such as automotive design, healthcare, military applications, and enhancing consumers’ in-store experiences.
3. Computer Vision in Interactive Media
Interactive media refers to using various devices such as controllers, smartphones, video game controllers, and eyewear like Google Glass to actively engage with and participate in interactive content, particularly with the rise of augmented reality (AR). In contrast to traditional TV and radio, which are passive forms of media consumption, interactive media offers a dynamic user experience by incorporating elements such as moving images, graphics, animation, digital captions, video, and audio. It allows users to interact and immerse themselves in the content actively.
AR revolutionizes media applications by providing an immersive experience. In its simplest form, AR allows users to connect and interact with individuals they wouldn’t typically have access to. In a more advanced scenario, it creates new worlds that closely resemble reality but are filled with virtual objects and possibilities.
This incredible experience is possible by combining real-time camera video input with image synthesis. This process overlays interactive graphics onto the physical environment, enabling AR.
Interactive media entertains consumers and finds applications in education, facilitating intelligent learning processes and museums and offering virtual tours and additional information about exhibits. It enhances these contexts by providing users a dynamic and engaging medium to explore and learn.
This incredible experience is possible by combining real-time camera video input with image synthesis. This process overlays interactive graphics onto the physical environment, enabling AR.
Interactive media entertains consumers and finds applications in education, facilitating intelligent learning processes and museums and offering virtual tours and additional information about exhibits. It enhances these contexts by providing users a dynamic and engaging medium to explore and learn.
4. The Sport of the Future: Drone Racing
In recent times, the popularity of flying drones has skyrocketed. The Drone Racing League (DRL) is at the forefront of this trend, dedicated to developing racing drones, hosting professional tournaments, and transforming AR-based entertainment into a competitive sport that blurs the boundaries between the physical and digital worlds.
A human operator of a racing drone utilizes an AR headset, which provides a first-person view and presents essential race-related information such as the track layout, live video feed from the drone, and performance statistics. However, advancements are being made to enable autonomous drone racing in the near future.
Each racing drone is an edge device, employing AI inference capabilities near the data source. This approach enhances data processing speed and eliminates hardware limitations associated with data transfer. To delve deeper into AI at the edge, refer to a previous article by InData Labs.
Each racing drone is an edge device, employing AI inference capabilities near the data source. This approach enhances data processing speed and eliminates hardware limitations associated with data transfer. To delve deeper into AI at the edge, refer to a previous article by InData Labs.
5. Tracking Stock
Regarding monitoring inventory, it is evident that technology has transformed imaginative concepts into reality. The advent of computer vision has played a crucial role in introducing augmented intelligence, empowering individuals to construct virtual realities with an abundance of unprecedented possibilities.
Presently, we are experiencing the integration of computer vision into various aspects of our daily lives, revolutionizing our interactions with the world. Machine learning and deep learning advancements have ushered in a new era of computer vision applications.
Certain applications, such as face recognition and surveillance, robotics in production lines, and streamlining verification processes, have become essential for businesses. While the media and entertainment industry may receive less attention regarding computer vision, it continues to embrace technological innovations to flourish and expand.
Certain applications, such as face recognition and surveillance, robotics in production lines, and streamlining verification processes, have become essential for businesses. While the media and entertainment industry may receive less attention regarding computer vision, it continues to embrace technological innovations to flourish and expand.
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