Realistic AR Furniture Previews with Image Segmentation

Based on Patent Research | US-11057612-B1 (2021)

For general merchandise stores, accurately placing virtual objects in augmented reality is key. Current methods struggle to position these objects relative to real-world visual cues. Image segmentation, a computer vision task, precisely identifies visually-demarked regions. This allows virtual objects to be placed accurately within those regions. Stores can then offer customers realistic previews of furniture in their homes. This leads to better customer experiences and informed purchase decisions.

SOLUTION OVERVIEW

Evolving from Manual to AI Placement

For general merchandise stores, image segmentation offers a solution to the challenge of accurately placing virtual objects in augmented reality. This technology works by carefully examining visual data to differentiate regions, like floors or walls. By understanding these boundaries, virtual furniture or decor can be placed with precision in a customer's view. This process involves analyzing the image, identifying distinct areas, and then creating a segmented map that guides object placement. This ensures realistic previews and enhances the overall AR experience for shoppers.

Image segmentation automates the process of identifying surfaces, integrating seamlessly with existing AR platforms. Think of a customer using a home decor app to visualize a new sofa in their living room. Image segmentation ensures the sofa sits realistically on the floor, not floating in mid-air. This leads to more informed purchase decisions and greater customer satisfaction. By providing accurate and realistic previews, general merchandise stores can improve customer engagement and build confidence in their online shopping experience.

HOW IT WORKS

Images Analysis = Object Placement

Capturing the Customer's Room

Capturing images of rooms is the first step. The system uses a device's camera to gather visual data of the space where a customer wants to place virtual objects. This image serves as the foundation for all subsequent analysis and placement.

Analyzing Images for Surfaces

Analyzing the image to identify surfaces comes next. The system uses computer vision algorithms to differentiate between floors, walls, and other objects in the room. This process creates a detailed understanding of the room's layout.

Creating a Segmented Map

Creating a segmented map for object placement is the third step. Based on the analysis, the system generates a map that highlights distinct areas within the image. This segmented map guides the accurate placement of virtual furniture or decor.

Placing Virtual Objects Accurately

Placing virtual objects accurately enhances customer experience. The system uses the segmented map to realistically position virtual items within the customer's view. This allows customers to visualize how furniture will look in their homes, improving their confidence in purchase decisions.

Potential Benefits

Realistic Augmented Reality Previews

Provides accurate placement of virtual objects in AR, ensuring furniture and decor appear realistically within a customer's space. This eliminates guesswork and improves the shopping experience.

Increased Customer Confidence

By accurately segmenting surfaces, the AI enhances customer confidence in online purchases. Customers can visualize products in their homes leading to fewer returns and increased satisfaction.

Streamlined Integration with AR

The automated image segmentation process works seamlessly with existing AR platforms, reducing the need for manual adjustments. This saves time and resources for general merchandise stores.

Data-Driven AR Experience Improvement

Image segmentation provides detailed spatial understanding that can be used to analyze product placement effectiveness. This data can inform future AR experiences and improve sales strategies.

Implementation

1 Software Installation. Install AR application, ensuring compatibility with store devices. Configure camera permissions for image capture.

2 Camera Calibration. Calibrate camera to accurately capture room dimensions. Test image capture in various lighting conditions.

3 Segmentation Verification. Process initial room images, verifying surface identification. Adjust segmentation parameters for optimal accuracy.

4 Object Integration. Integrate virtual object library into the AR application. Ensure objects are properly scaled and rendered.

5 Deployment and Testing. Test object placement in different room scenarios. Gather user feedback for continuous improvement.

Source: Analysis based on Patent US-11057612-B1 "Generating composite stereoscopic images usually visually-demarked regions of surfaces" (Filed: July 2021).