How to Build a Visual Search Engine
Over the past decade, the search engine industry has been able to cover great strides in its development. Today's businesses can fully enjoy the benefits of personalization, the development of natural language processing technologies, and multimedia search. However, the potential of visual search, taking into account the role of images in our lives and in business, is still not fully recognized.
Huge companies have already implemented this approach (for example, Google Vision, Vision Microsoft). Archer Software was also fortunate enough to take part in the development of visual search technologies in 2015. Together with the company TVRunway, we created a system that allows you to check the presence of a particular model of clothing in more than 300 stores, and immediately purchase it. Today, we want to take visual search another step. Let us tell you about the possibilities of visual search for business, and how to implement it with maximum benefits.
How Can Visual Search Be Used to Gain Maximum Business Benefits?
In the modern world, where instant satisfaction is at the forefront of marketing trends, visual search is a welcome innovation. Any obstacles between internet surfing and buying are completely erased. Many online stores in the western hemisphere are adopting visual search engines, and creating advertisements and catalogs according to the requirements of the visual network.
For e-commerce, the use of visual search means the growth of "hot" sales carried out "on the spot." It is much easier to encourage a buyer to purchase goods at the highest moment of interest. Buying goods through a traditional search, when options are limited to the first ten results, no longer satisfies progressive audiences. Now it is possible to take a picture of your favorite thing, compare analogs with the help of recommendations, and immediately make a purchase. Just take a look at the statistics supporting the effectiveness of visual search.
- For 74% of users, according to the results of research, traditional keyword searches turn out to be ineffective when there is a desire to find a certain product. People really are not really able to describe things absolutely in words.
- According to another study, people are 48% more likely to click on products that are selected based on a visual search, and they make repeat purchases 75% more often. The average checkout value also increases by 11%.
The most promising but controversial visual search option is the search for people. Pages on social networks contain enough data about each person – photos, real names, surnames, emails, phones, etc. This innovation provides an opportunity to get all the information about a person, just by pointing a camera at a face. This could be done, for example, with the help of the Recognizr mobile application from the Swedish company TAT. However, the idea is rather ambiguous from an ethical point of view, but it definitely could give the world a new level of security.
Additionally, visual search technologies can be implemented for the following purposes:
- Security. For example, a video recognition system embedded in a “smart home” system can recognize the identity of someone who has approached the entrance doors and either allow him to enter it or not.
- Honest results of sports competitions. The system is able to track all the movements of each of the athletes during a match, a fight or other sports activity.
- Successful and quick police investigations. The system can identify offenders if their data is contained in the database.
- Identifying celebrities and other public figures. The system could assist media and news agencies’ timely reactions in case of interesting and politically important events.
- Image recognition online. This could make shopping more pleasant, effective and thoughtful.
It is obvious that the sphere for the application of visual search technology is very wide, from tasks in the fields of medicine, geology, security, and protection of copyright, to simple requests from ordinary internet users.
Programming Artificial Intelligence on Object Recognition
In order to turn the recognition of objects in an image from an idea into reality, it is necessary to use machine learning, such as neural network learning. Such projects as Clarifai and Slyce are based on this concept.
First of all, you will need to prepare source materials – for example, several thousand images of a particular object in different positions and on all kinds of backgrounds. Since the buyer will mainly take photos from the phone, many factors should be taken into account when preparing and training the neural network, such as:
- Bright or dim lighting
- Bad angles
- Blurry images or inscriptions
- Distracting backgrounds
- Photos with perspective
Some of the main technologies which a program for object recognition can be built on are:
- TensorFlow, a machine learning framework that allows you to create a neural network
- Google Cloud Vision
- Soundex for visual recognition of objects
Object-recognition-by-photo systems are essentially API services, and are easily integrated with chat bots, websites, mobile applications, or a company's internal systems. This will allow it to function without human intervention as a fully automated process. The order immediately after completion will be sent to the appropriate department of the company and can be processed as soon as possible.
It is safe to presume that within a few years, consumer internet will be completely different – the bulk of content will be images and video, and search engines will be able to find the information users need based on visual similarity, rather than textual descriptions, as the human brain does.
Do you want to realize all the possibilities of visual search innovation for your business? Then you’re in the right place. Archer Software is ready to help with the development of a visual search engine so your clients get the most progressive experience, and you get the highest returns.