In image annotation there are various techniques to annotate the object of interest for machine learning and deep learning. Though, there are different technique and bounding box annotation is one of the well-known technique to draw with rectangles from one corner to another for right object detection.
How Bounding Box Annotation is done?
In bounding box annotation, is used to annotate with rectangular drawing of lines from one corner to another of the object in the image as per its shape to make it fully recognizable. 2D Bounding Box and 3D Bounding Box annotation are used to annotate the objects for machine learning and deep learning.
The main purpose to reduce the range of search for the objects features and reducing the computing resources. And apart from object detection it also helps in object classification.
Bounding Box for Object Detection
When bounding box annotation is used, annotators simply outlines the objects, as per the requirements of the projects. In various scenarios or computer vision based model development, like autonomous vehicle, it only searches the object comes while running on the street.
Bounding box annotation contains the coordinates that has information of where exactly the object resides in the image. And the image shows the coordinates of the bounding box annotation. For an example, to find a car in the image, the algorithms tends the system to view only inside these coordinates instead of looking at the entire image for the car.
However, only bounding box cannot help the model to predict the object detection with 100% accuracy. For this you have to used huge quantity of training data to improve the object detection accuracy with different types of similar objected annotated with bounding box annotation.
Bounding Box for Object Classification
Bounding box annotation is also used to classify the objects using the conventional neural network techniques. As the bounding box annotation categorized the object and locate the same in the image. Hence, object detection is the combination of object detection and classification with localization.
Bounding box annotation is used in self-driving cars based model development. As it help to detect the objects with classification and localization of the same. However, there are more image annotation techniques for object classification used as per the different model perception needs.
Algorithms using Bounding Box Annotation for Object Detection:
In the machine learning training there are different types of algorithms (listed below) used to train the models. And out of them many of them are using the training data sets created with bounding box annotation for object detection for different types of objects in different scenarios.
Algorithms using Bounding Box Annotated Images for Training Data:
- Faster R-CNN
- Fast R-CNN
- Feature Pyramid networks.
- Yolo Framework – Yolo1, Yolo2, Yolo3.
Bounding Box Annotation Use Cases
Bounding box annotation image annotation techniques is first choice of the machine learning engineers when they are looking for machine learning training data. So, righty here bounding box annotation is used to create datasets for what type of machine learning or AI model. You can find below the industries, models and area where bounding box annotated images are used to train the models.
- Self-driving cars
- Fashion & Retail
- Medical & Diagnostics
- Security & Surveillance
- Autonomous Flying Objects
- Smart Cities & Urban Development
- Logistic Supply & Inventory Management
These are the AI models, industries and fields, where AI based models are used to detect the objects with training data created through bounding box image annotation techniques. In all use cases, machine like robots, autonomous vehicles or robotics needs to precisely detect the object through computer vision. And bounding box annotation is one of the best one provides the accurate details.
How to get Bounding Box annotated training data?
Annotating the object in the image with bounding box annotation seems easy, but if you need huge amount of high-quality training data sets you need to consult with the right partner who can annotate the data for you. Anolytics is one them provides, image annotation services for machine learning and AI. It is also providing the image bounding box annotation service to annotate the different types of objects in machine learning with next level of precision to produce the quality training data sets.