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  • Artificial Intelligence
  • Image classicifation
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Technology

Fundamentals of Computer Vision in Retail

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Artificial Intelligence (AI)
Artificial Intelligence is a set of algorithms which simulates human-like intelligence
Image Classification
A process in which the AI assigns categories within images based on its relevancy
Object Detection
The AI localizes objects within an image and identifies them into categories
Multi-Object Tracking (MOT)
AI tracks multiple products that are seen within a video
Action Recognition
Classification of any activity of a person or a group of people based on video sequences of their actions
Data Anonymization
AI technology removes all personal identifiers as well as private or confidential data

Artificial Intelligence (AI)

Artificial Intelligence is a set of algorithms which simulates human-like intelligence. Computers can be programmed to analyze, learn, and understand (and/or solve problems).

Checklens’ AI-technology powers cameras that can to automatically detect any type of product in any store within fractions of a second. The AI instantly recognizes a product when it enters the camera's field of view.

Artificial Intelligence (AI)
Use Cases
The camera is installed above a shelf or at checkout
The camera upgrades with Checklens AI
The camera is able to detect any product in a store

Image Classification

The process of categorizing and assigning a label to a given image.

Checklens AI assigns a category to each recognized product. Products are only recognized, not counted during classification.

In this way, Checklens’ Solutions are able to assign items to their categories, e.g., when recognizing fruits and vegetables in Checkfresh.

Image classification
Use Cases
Checklens AI recognizes each product
Checklens AI assigns label to each product
Checklens AI is able to detect a specific product

We define three different types of image classification:

Binary Classification

In effect when we want to predict if an image belongs to a particular category or not, e.g., the AI technology tells us if there is a product on the image or not, without identifying the particular type of product

Multi-Class Classification

Output of a specific class among a set of available options. E.g., Checklens AI tells us the product’s ID from a range of products in a store.

Multi-Label Classification

Assignment of a set of labels to an image which might not be mutually exclusive, e.g., Checklens AI tells us all the colors that are seen on an image or tells us if a main dish or a side dish on a plate is seen.

Object Detection

The process of estimating the location of objects in an image and identifying their classes.

Checklens AI combines the localization with the classification of a recognized product. Usually, location is described in terms of the object’s bounding box.

This allows Checklens’ Solutions to analyze discovered items in the first place.

Object detection
Use Cases
Checklens AI combines the location and the classification of products
Checklens AI detects products

Multi-Object Tracking (MOT)

Estimating trajectories of multiple target objects in a given video sequence.

Checklens AI tracks multiple products that are seen within a video. A model is developed in order to link detections across each frame and to generate object trajectories. Hence, this allows us to automatically track products in each video.

This allows Checklens’ Solutions to detect "non-scans" or "miss-scans" of the tracked items.

Multi-object tracking (MOT)
Use Cases
Checklens AI tracks each product
Checklens AI is able to recognize moving products e.g., items at the checkout

Action Recognition

Classification of an activity of one or more subjects based on a video sequence of their actions.

Checklens AI classifies certain activities of a shopper or a group of shoppers, e.g., shoppers standing in front of a shelf, shoppers taking products off a shelf, a customer scanning products at a self-checkout, shoppers passing products to other shoppers or customers placing products into a shopping basket, back onto the shelf etc.

This allows Checklens’ Solutions to use customer behavior in order to analyze "non-scans" or "miss-scans."

Action recognition
Use Cases
Shopper grabs product from shelf
Shopper passes product to another person
Shopper puts product into shopping cart

Face and Other Personal Data Anonymization

Removal of all personal identifiers (e.g., eyes, ears, the entire face) and private or confidential information (e.g., credit card details) from raw data in order to keep all shoppers anonymous throughout the entire store visit.

Checklens AI uses an automatic anonymization system. Regions containing facial information and visible personal/sensitive data are automatically replaced with blurred regions. Therefore personal data is neither recognizable for human intelligence nor for artificial recognition systems.

Face and other personal data anonymization
Use Cases
Checklens AI automatically removes all personal sensitive information
Anonymization is continuously guaranteed
Checklens AI is GDPR compliant
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