How Image Annotation is Pushing Forward Object Detection in AI

image annotation Nov 17, 2020

A car stops automatically as a pedestrian crosses the road, a drone notices that a cow has gone missing from the herd, a medical Artificial Intelligence (AI) detects a treatable abnormality. In each case an AI system is identifying an object, locating it in an image and then assigning it a label. Together these tasks are known as object detection.

In order to accurately spot the objects that matter in an increasingly complex and dynamic world, AI systems need to be trained with large and precisely labeled image datasets. Image annotation for computer vision is therefore an increasingly vital component of AI development. Commercial image annotation companies, like Keymakr, are allowing machine learning pioneers to refine their models by taking on the burden of annotation and quality control. This blog will focus on four image annotation services that are helping transform object detection AI for a variety of industries. What are the image annotation types? How do these different forms of annotation support the development of machine learning?

1: Bounding Boxes for Autonomous Vehicles

Bounding boxes are the most simple type of image annotation. An annotator or an AI image annotation tool selects coordinates for a two dimensional box to cover a specific object. When all of the relevant objects in the image have been identified with boxes the data can then be used for machine learning. This type of annotation is ubiquitous, due to its speed and simplicity.

Training datasets for autonomous vehicles employ a great deal of boundary boxes. These images allow vehicle AI systems to locate and identify other cars and distinguish between road signs and pedestrians.

Bounding Boxes | Keymakr

2: Polygon Annotation for Medical AI

Polygon annotation is a way of increasing the precision of annotations by more accurately defining the shape of objects. When an object is of an irregular shape it is possible to plot vertices around an outline and link them together with lines. This technique is slower than bounding with boxes but eliminates some of the noise that can potentially confuse a model.

Polygon Annotation | Keymakr

Polygon annotation has been profitably used in the field of medical AI. Medical AIs can learn to identify many parts of the anatomy from detailed polygonal annotations. AI computer vision has even been deployed to find tumors in MRI scans.

3: Semantic Segmentation for Smart Agriculture

Semantic segmentation provides fine grain precision in image annotation. In this technique an image is divided up, pixel by pixel, into specific labels. For example, every pixel that forms a car in the image is distinct from each pixel forming the road and so on. Semantic segmentation is therefore able to provide another layer of detail in annotation. It is also labour intensive and time consuming. However, image annotation outsourcing companies, such as Keymakr, are now able to scale up this level of annotation for the needs of researchers.

The applications of semantic segmentation for computer vision training include real time crop monitoring in the agricultural sector. AI systems are now able to inform farmers when their crops are being attacked by pests and disease allowing them to act before too much damage is caused.

4: Video Annotation for Security

The sheer number of frames contained in even short amounts of video footage presents significant added complexity in comparison to single image annotation. Annotating each frame means a colossal investment of time and resources that can be prohibitive for developers and distract from their ultimate goals. Image annotation services have responded to this challenge by developing bespoke data annotation tools, allowing annotators to provide faster results tailored to the requirements of any project.

Video Annotation for Security | Keymakr

Real-time security data annotation allows computer vision to identify potential threats before they can escalate. AI-based video analytics can recognize firearms or dangerous objects and then alert camera operators who can then coordinate a response. Advanced warning systems such as these have the capacity to limit harm to individuals and protect property.

Image Annotation for Machine Learning
Keymakr is your image annotation solution. Take advantage of cutting-edge tools and an experienced and well managed team of annotators. Contact a team member to book your personalized demo today.

pixel-perfect image and video annotation
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