What does object segmentation aim to achieve?

Object segmentation primarily focuses on the process of dividing an image into segments that correspond to different objects or regions within that image. The goal of this technique is to group together pixels that belong to the same object, making it easier to analyze or manipulate those objects distinctly. By achieving this, object segmentation assists in tasks such as identifying boundaries of objects and distinguishing one object from another in image processing and computer vision.

This technique is critical in various applications, including autonomous vehicles, where identifying the exact location and shape of objects is necessary for navigation and safety. It allows systems to understand their environment more effectively, improving interaction and response to the surroundings.

The other options do not correctly capture the essence of object segmentation. Identifying device connections and classifying IoT devices pertain more to network topology and device management rather than visual data processing. Aggregating sensor data deals with data synthesis from multiple sources, which does not relate to the visual analysis of images and segmentation of objects within them.