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Face Filters

              Face filters in Computer Vision are fun and interactive tools that uses algorithm
              to detect and track facial features, such as the eyes, nose, mouth, and overall
              face shape. This process is called facial landmark detection. These filters then
              overlay digital effects or objects on a person's face in real time, such as hats,
              glasses,  or  funny  faces.  They  are  commonly  used  in  social  media  apps  like
              Instagram and Snapchat, video conferencing platforms, and Augmented Reality
              (AR) applications.

              Google's Search by Image

              While most people use Google to search for information
              by  typing  text,  there’s  an  interesting  feature  called
              Search by Image  that  allows  you  to  search  using  an
              image instead of words. This feature relies on Computer
              Vision, a technology that enables computers to interpret
              and analyse images.
              When you upload an image to Google Search, the system
              uses Computer Vision Algorithms to analyse the image. It
              extracts key features such as shapes, colours, textures, and
              patterns. This process is similar to how the human brain
              identifies objects by recognising visual characteristics.

              Next, Google compares these extracted features to its massive database of images collected from across the
              Internet.  Using  advanced  algorithms,  such  as  image  similarity  search  and  pattern  recognition,  it  identifies
              matching or similar images.

              Once the analysis is complete, Google displays search results that are related to the uploaded image. These results
              may include:
                 • Information about the object or scene in the image
                 • Similar images
                 • Websites containing the image or related content
              Computer Vision in Retail                                                     Person

                                                                                                 Person
              In the world of shopping, both online and in physical stores,
                                                                                     Person           Person
              Computer  Vision  is  being  used  more  and  more  to  improve              Person
                                                                              Person
              the shopping experience and make businesses more efficient.
              Retailers  are  using  this  technology  to  understand  customer
              behaviour, optimise store layouts, and provide better services.

              It helps the retailers to have:
                 • Improved store layout: By analysing where customers spend the most time, retailers can modify store layouts
                to boost sales and enhance the shopping experience.
                 • Better inventory management: Retailers can track product engagement to determine which items attract
                more attention and which do not, optimising stock levels. Additionally, Computer Vision can assess shelf space
                usage to identify inefficient configurations and recommend improved product placements.
                 • Enhanced customer experience: Computer Vision facilitates personalised recommendations and streamlines
                the shopping process, making the overall experience smoother and more enjoyable for customers.

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