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4 new real estate solutions created using computer vision: 2021 edition

Computer vision obtain data and information, also enables a machine or computer from multi-dimensional data sources to transform into valuable insights. Image recognition systems based on computer vision technology are being tested in many industries – and real estate is one prime example.

What is the basic meaning of computer vision?

Computer Vision is a field of artificial intelligence associated with video and image analysis that enable computers to “see” the extract information just like human eyes would see them – or rather even more precisely than human eyes would. It’s based on specialized software that identifies and classifies objects. In addition, computer vision can analyze images (photos, pictures, videos, barcodes), faces and emotions. Millions of pieces of data are collected to isolate features and combinations of elements to identify similar objects further.

Leading Computer Vision Startups

Computer vision is perfect solution to propel real estate’s growth – it speeds up processes, analyses areas that are difficult for humans to reach physically, or check the interior through 3d vision. Real estate sector slowly adapts to the world of data-focused decision making, and Computer Vision is a tool to make it happen.


Matterport’s Cortex artificial intelligence is a deep learning neural network that creates robust 3D spatial data from a wide variety of capture devices including Lidar cameras, the Matterport Pro2, 360 cameras, and even smartphones. Cortex enables a host of powerful features to enhance the value of your digital twin. These include: automatic measurements for any room or object in the room, automatic 2D-from-3D HD photo gallery creation, auto face blurring for privacy protection, custom videos, walkthroughs, auto room labeling, object recognition, and so much more. 



Zillow has recently launched 3D Home, an AI virtual viewing service application in the United States and Canada. Buyers can use Zillow’s application to view the house in a 3D tour. For sellers, 3D Home uses the iPhone camera. Zillow says it’s now leveraging computer vision to improve the accuracy of its Zestimate appraisals. The Seattle, Washington-based real estate management and listings company launched a new benchmark that considers homes’ visual highlights in tabulating property prices and then adjusts those estimates for locations on the market to account for real-time sales data.

Zestimate now leverages AI models trained on millions of photos from sellers, listing agents, and homeowners. It’s tuned such that highly desirable and in-demand features, like new granite countertops and remodeled bathrooms, have a greater pull on a home’s estimated market value. Even natural light and curb appeal make a difference, according to Zillow, as do touches like high-end finishes, fireplaces, remodeled kitchens, updated fixtures, and well-manicured lawns.



Tractable develops artificial intelligence systems for accident and disaster recovery. Working with a leading global insurer based in Japan, Tractable will soon help homeowners recover faster from a typhoon by allowing them to submit photos and obtain an AI-accelerated claim payout. With AI property, insurers can immediately assess the extent of damage from photos or videos sent via a smartphone app.

No time is lost waiting for an appraiser to visit the property. Policyholders have the reassurance of being served straight away, insurers can bring speed and precision to every claim, and urgent cases can be prioritized for swift settlement and repairs.


Houzen’s AI Valuation is based on multiple historical and real-time data sources gathered together to draw inferences and train AI and computer vision models. These sources comprise of UK’s real estate marketplaces (such as Zoopla, Rightmove), property data aggregators and statistics providers (such as PropertyData, Land Registry). Further, Houzen’s proprietary closed deals data, collected over the years, plays the role of secret sauce in price prediction analysis.

Computer Vision collects billions of features and amenities data points from the property images that facilitate feature engineering. Houzen firmly believes that highly accurate data is the key to an accurate AI prediction model. Amenities, floor area and location details are fetched and aggregated through language preprocessing techniques. The aggregated data is structured, analysed, preprocessed, cleaned and feature engineered with precision before feeding to machine learning algorithms. Periodically, the models are updated with latest property data to capture all ongoing trends in the market.


What does it mean for you?

If you decide to value your property using houzen’s Valuation tool, the Computer Vision will assess everything that’s visible on your property’s pictures and take them into consideration for the final price recommendation – even if it’s not mentioned in the written description. This makes houzen’s valuation much more precise and complete than a classic or instand valuation.

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