Case Study: Strategies for Accurate Small Object Detection in Images
Introductory Insights:
One of the most challenging and significant issues in computer vision is the detection of small objects. To reliably identify small things in a video feed or image, you must solve the computer vision problem of small object detection. The size of the thing itself is not a requirement. In aerial computer vision, for instance, it’s essential to be able to reliably identify objects even if each one will be small in relation to the scale of the photo.
Small object detection, therefore, is a challenging task in computer vision because apart from the small representations of objects, the diversity of input images also makes the task more difficult.
The Complexities of Detecting Small Objects in Computer Vision:
If the resolution is poor, the detector may have trouble detecting small things, and there won’t be much visual information available to pinpoint the locations of small items. Additionally, small things may be able to distort or overlap with other objects.
Here are some factors that make small objects hard to detect.
