Computer Vision can be broadly defined as the processing of images so as to interpret the objects contained in them. With recent advancements in image processing, machine learning, and cognitive computing, computers are able to simulate the human visual sensory process to a large extent. The advancements in these areas in recent years have helped computer vision reach maturity levels that are several orders of magnitude advanced than what was possible even a decade ago.Computer vision is widely used in several industrial and consumer applications today. Face recognition for accessing a personal computer, tagging individuals on photos, use of robotics in manufacturing automation and quality control, analysing patient condition through remotely uploaded images, home security solutions that distinguish familiar faces from those of strangers, etc., all apply the concepts of computer vision. Autonomous, smart cars and associated technologies rely heavily on sophisticated computer vision algorithms that are still in the advanced stages of development. With the seemingly unending possibilities that computer vision offers, it is only natural that billions of dollars are invested in advancing the boundaries of this technology. The amount invested is expected to go up from USD 7 billion in 2015 to USD 50 billion by 2022, at a CAGR of 30%+ .

How is Computer Vision relevant to Real Estate?
Technology related to computer vision is making inroads into all areas of human interest, and Real Estate is no different. The recent advancements in computer vision are helping players in the industry unlock areas which have hitherto been considered impossible to achieve as a scalable solution. With the availability of significant computing power at costs that are getting reduced every quarter, the applications of computer vision is expanding at a fast pace in the industry. Some of the important applications of computer vision in Real Estate are given below.

 

  • Unlock listing data through photos
    According to a blog from T3Sixty.com , computer vision can help reveal hundreds of property attributes from listing photos that are typically not captured as part of the listing information. Users will now be able to understand factors that are subjective, such as the quality of natural light and vastness of the view without even stepping into the property.
  • Transform listing search to searchable images
    Users would be able to list properties using specific image characteristics, rather than what has been traditionally done using quantifiable property attributes such as beds, baths, living area etc.
  • Identify matching properties quickly
    Image based search would be able to identify properties that display similar characteristics on a whole set of attributes. Agents would be able to match properties with nuanced attribute descriptions leading to more productivity and customer satisfaction.
  • Create property details for listing just from images
    In the future, agents would be able to generate entire property details and room-wise amenities list by just uploading a set of photos. Computer vision will enable recognition of the elements contained in these images, demarcate them, and create listing information that can be uploaded directly into an MLS or a listing platform.
  • Sequence property images in a pre-defined order
    Typical MLS listings have photos of properties in a haphazard order which do not follow a sequence. Through computer vision, listing agents would be able to sort the photos quickly and efficiently in a pre-defined order before uploading to the listing platform. By adding image quality filters to this process, photos which are not good can be marked out for replacement or deletion.
  • Compare properties room-wise
    Computer vision can be used to compare multiple properties room for room in terms of space, relative location of windows and doors, natural lighting, etc. Multiple images for the same room, if available, can be grouped for better comparison and assessment. All this is possible on listings that have been entered years ago since images can be processed real-time. This can create a compelling user experience for the property buyer.

 

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