botspot, the maker of the full body scanner BOTSCAN NEO, has achieved full workflow automation, accuracy and scalability by integrating with 3D Measure Up body measurement extraction software and botspot’s. The key benefits for the users using this integrated technology solution are:
• Scan time 0.1 seconds
• Measurement accuracy ±1 mm (externally verified)
• Automatically extract over 200 body measurements
• Scan-to-Measurements in less than 5 minutes
• Fully automated process
The general workflow is depicted in the picture below:
The BOTSCAN NEO includes the following components:
• ~124 Canon cameras
• White aluminum enclosure
• Lighting (indirect ambient and controlled flash)
A high-performance computer for controlling the scanning process, image acquisition, and generation of the 3D models
• Push button scanning
• Automated 3D reconstruction via scripted RealityCapture
The keys features of 3D Measure Up are:
• Identify over 200 body landmarks and extract measurements including not just heights and lengths, but also convex and along surface tape measures, vernier caliper distances etc.
• 3D Measure Up follows definition from ISO, Bufar, IEEE standards.
• Automate workflows there by increasing speed and accuracy. It takes less than 30 seconds without any human input.
• Maintain confidentiality by having no human involvement in the process.
• Several uses in the fields of medical, health, ergonomics and apparel.
• Provides data via a web application, REST API, and OEM widget.
The accuracy of the system’s measurements can be checked using external calibration references, such as calibrated mannequins or scale bars. Such processes can be automated to do calibration checks or recalibrations regularly.
The NEO’s colossal size and substantial build make it possible to maintain precise calibration standards for one’s day-to-day activities. Sturdiness is critical because the scanner’s enclosure surface is where botspot calibrates the scanner. Don’t forget that the NEO is a precise measurement tool, and its design is based on this purpose.
When using 3D Measure Up, even the method a user scans affects the accuracy of their extract measurements. In order to get the most accurate results, whole-body scans must be taken instantly via synchronised camera triggering, as a person’s body is in motion even while they are standing still. The NEO’s pure photogrammetry scan permits a full body scan in 0.1 seconds, making it a significant design element.
Body landmark identification is not always a perfect science, hence 3D Measure Up uses a mix of geometry, computational, and machine learning (ML) algorithms to automatically do by providing accurate and reliable results.
Optimal landmark detection is one example of scan optimization for measurement extraction. Figure 4 shows the surface lengths of the left arm and shoulder interpolated between landmarks. That is, accurate measurement extraction requires precise landmark detection. This prompts the issue, “How do we optimize landmark detection?” The aim is to produce clean models with clearly specified attributes. The 3D model must have accurately defined arms, elbows, and hands to get accurate arm measurements.
Contrary to the film industry, a whole-body scanner for body measurement extraction is optimized for pristine characteristics throughout the body.
A person’s body changes in size throughout the day. One is taller in the morning, bloated after eating, and simply breathing causes dimensional changes in the chest cavity. botspot has found that taking 4 scans within a 1 – 2 minute period provides more robust and reliable measurements because of the following reasons:
• Detect and correct for outliers in the measurements
• Average out breathing patterns
• Simple redundancy
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