Computer Vision Applications In Design- A Tool In The Creative Arsenal

Computer Vision Applications In Design- A Tool In The Creative Arsenal

Can you imagine a machine replicating tasks of human vision? Yeah, that’s right, we are progressing towards a future where computers would have the capability of carrying out identification tasks. With the advancements in Computer Vision applications in design and techniques, machines will automate human vision tasks making our lives easier.

What is Computer Vision in Design?

Computer Vision aids computers to take actions or in making decisions based on the meaningful data acquired from digital images, videos, or any visual input.

Additionally, it develops the artificial intelligence of computers to automate them to see the world as we humans see it.

We humans input visual data through our retinas to recognize and identify objects. Similarly, computers make decisions based on pre-fed data in the form of digital images and videos by interpreting or translating them.

Starting in the late 1960s, computer vision aims at empowering computers to extract 3D features using 3D scanners. They plan to do it by devising an algorithm that inputs real-time videos and photos to make a decision or take appropriate action.

The developments in the field of computer vision are going to open new avenues which will transform our lives and future for the better.

Why Computer Vision in Design?

The need to manage data is ever increasing with more than 3 billion images shared worldwide. Moreover, managing digital data or analyzing visual inputs is difficult.

However, with computer vision, these human vision tasks can be automated.

Additionally, computer vision plays an important role in the industry related to facial recognition. Using computer vision, theft detection becomes a piece of cake. Also, companies can use it for biometric authentication by facial recognition to verify employees.

Many companies are using computer vision for license plate recognition, for recognizing characters [OCR], and for sending real-time alerts using intelligent video analytics.

Computer vision plays a significant role in the field of interior design. Computer vision aims at bridging the gap between clients and designers. It will enable clients to explain their vision to designers by laying down their preferences and enable designers to explain their vision to clients.

With 3D scanners, an area can be scanned, and computer vision algorithms can be used to recommend interior designs using machine learning and deep learning. It can take preferences from customers and customize designs for them or can match designers specializing in their tastes.

AI and Interior Design

Artificial Intelligence has its application in almost every industry and interior design is no exception. The communication gap between a client and a designer has been bridged with the innovation in AI. This is because clients can now understand a designer’s visualization and make the designer understand their vision or ideas.

The main issue in traditional interior design is communication. Designers meet the client to discuss a particular design and then the client suggests some alterations. Also, this happens a few more times and is a tedious process.

Moreover, it’s error-prone because of any miscommunication as the designer might get confused with the instructions as it’s a manual process.

Whereas, with AI designers can get the designs approved from the comfort of their home and incorporate the alterations.

Applications of Computer Vision in Interior Design

1. Have you ever liked a particular design in a photograph but faced difficulty in searching that product online?

With computer vision and deep learning, you could visually search for similar products on the internet and order them. Visual search algorithms match in situ images with different backgrounds with iconic product images that have a white background. Moreover, automated tools are in development that can suggest designs or ideas based on your search.

2. Traditional CAD software used for interior designing are less efficient and time-consuming.

Instead, we can use computer vision algorithms for accelerated, more efficient and accurate interior designing. The computer vision approach includes the use of efficient image segmentation and objects classification algorithms for the effective identification of objects in an interior image.

The next step includes color assignment based on the client’s preference which is achieved using a Graphical User Interface (GUI).

Graphical User Interface

GUI suggests and customizes different color schemes to create new color combinations suitable for the interiors.

  • Furniture is one of the most crucial design elements when it comes to interior design.  To analyze different features of furniture in an interior setting we use many machine learning methods. These features may include color, size, material, etc.

Computer vision with a deep learning-based approach enables computers to learn the features of the furniture and its design styles. This, in turn, will help clients search for such designs and styles of furniture for their interiors.

  • Designers use Computer Vision to analyze thousands of images and videos and record insights from each one of them.

AI collects data from clients to know their preferences, assist designers to incorporate trending designs, color schemes and better object positioning.

This reduces manual processes which are both time-consuming and resource intensive. It also replaces the research part by providing access to a much larger library of designs from all over the world.

The clients get to customize every bit of their designs and incorporate the ideas suggested by the designer.

Design is a creative task, and it must have a human element attached to it.

However, with AI and Computer Vision we are bridging the gap between the client’s ideas and the designer’s visualization.

Moreover, we apply Computer Vision in all aspects of interior design from 3D scanning of interiors, object placement, design suggestion, color themes and more.

In the future designs will be approved and finalized without any manual work or travelling. Designers would send their visualization using 3D renderings and clients would approve or suggest amendments to personalize their interior design.

Learn more on how Tooliqa is developing this technology here.

Tooliqa specializes in AI, Computer Vision and Deep Technology to help businesses simplify and automate their processes with our strong team of experts across various domains.

Want to know more on how AI can result in business process improvement? Let our experts guide you.

Reach out to us at business@tooli.qa.

Also read: A guide to computer vision platforms | Insights - Tooliqa

FAQs

Quick queries for this insight

What are some potential benefits of using Computer Vision in design?
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By improving and reducing overall lead times, AI may help design teams. It can also broaden their creative discovery by using computer vision to analyze and remember insights from thousands of photos and videos. Additionally, these designers may more quickly figure out how to include popular colors, patterns, and fashions.

What are the bottlenecks in traditional interior design?
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Interior designers face the issue of multiple reiterations on the same design plan which results in added time and resources in developing the updated versions. There is also a chance of miscommunication which can result in wrong designs being developed.

How does computer vision aid interior design?
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Computer vision aims at bridging the gap between clients and designers. It will enable clients to explain their vision to designers by laying down their preferences and enable designers to explain their vision to clients. With 3D scanners, an area can be scanned, and computer vision algorithms can be used to recommend interior designs using machine learning and deep learning. It can take preferences from customers and customize designs for them or can match designers specializing in their tastes.

Connect with our experts today for a free consultation.

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