3D cuboids are familiar with bounding boxes with additional in-depth information about the object. Thus, with 3D cuboids you can get a 3D representation of the object, allowing systems to differentiate attributes like volume and position in a 3D space. A use-case of 3D cuboids is in self-driving cars where it can use the depth information to measure the distance of objects from the car.
This is an annotation process which involves task labelling objects in 2D images with cuboids. The 3D cuboids help in determining the depths of the targeted objects such as vehicles, humans, buildings etc. It is used for building a 3D simulated world from 2D information which is captured by cameras. The training data helps to train the Cuboid detection models which help in concentrating the object of interest in the world and in calculating the different poses.
Following are a few examples of Use cases in the real world:
- Cuboid Annotation really helps self-driving vehicles to understand the real-world environment. Its main function is to help detect vehicle movements and its dimension for self-driving vehicles. It also helps self-driving cars to measure the distance of each obstacle from the vehicle and calculate the spacing.
- This is a very important reason for the machine to understand as the self-driving vehicle has to always calculate what to do in a traffic congestion, measuring the distance from other cars who are parked in front/back/right side / and left side.
- A wrong calculation could end up in an accident of the vehicle and the entire process goes to waste. That is the reason why the algorithms which are being fed to the machine must be accurate.
Identifying Indoor Objects
- We always have the ability to build modular perceptions from our own knowledge for detection of household indoor objects using the 3D cuboid annotated images. This aids in training our computer vision models to have in-depth object detection capabilities.
- When we mean indoor objects, it could be anything inside a home or office, basically something which is inside a particular structure.
- Cuboid annotation helps in identifying objects like couches, tables, wardrobes, with precision and best clarity.
Training Robots in Different Industries
- Cuboid Annotation can be efficiently used in training robots that are deployed in different industries such as automotive and warehousing.
- It helps in building better perception models that enable the robot to work continuously without the need for human interference.
- This enables the industries to operate 24hrs without any closing and makes the work faster and better. This also improves the Global markets where there is a constant rate of production & supply in order to meet the demands.
- The 3D cuboid annotation of images captured from 2D cameras boosts the power perception of robots and drones which are applicable in various fields.
3D cuboids are similar to bounding boxes but provide additional in-depth information about the object. Thus, with 3D cuboids we get a 3D representation of the object, allowing systems to distinguish features of volume and position in a 3D space.