Bounding boxes, also known as annotations, are used in image recognition and machine learning to denote boundaries around an object or region in an image. They can be applied to regions with diverse shapes and sizes by means of digital curve tracing, manually-defined contours, or a combination of both. Annotations provide useful statistical data pertaining to shape, size and orientation that aid in recognition of the object or region via powerful machine learning algorithms. Furthermore, they can also be used for various tasks such as fingerprint identification and facial recognition. Overall, bounding box and annotation techniques are essential tools when it comes to modern computer vision strategies.
Bounding Box and Annotation are the deliverables creates information and hot spots to enable data management and image analysis through objects, features, elements that can be easily detected and recognized. We handle as many cases including various languages, maps images, aerial images, detailing images and domain specific images. We have done image tagging for remote sources such as self-driving cars, live video footages, drone images etc.
Bounding box and annotation service included localization and object detection in images and videos. Our Image annotation solution enables you to annotate bound boxes with highest-quality precision which enables you in building state-of-the-art computer vision models.
Some of the domain areas we work on helps traffic, retail, driverless cars etc. We analyze traffic load on a particular road segment using our tool, annotate all the objects like car, truck, bus, etc. related to traffic.