<p>Based on the resolution of your sample, I can say that it's a crop from much larger image, therefore the ball in its given context it's fairly small object.</p>
<p>Yolo architectures are notorious for poor performance on small objects due to their reduced dimensionality in the feature maps.</p>
<p>For tracking detecting and further tracking small objects I recommend using an <a href="https://arxiv.org/pdf/1512.02325.pdf" rel="nofollow noreferrer">SSD</a> architecture which uses to feature maps extracted from multiple depth levels for producing the results; or maybe try out a newer architecture that can equal inference time performance such as <a href="https://arxiv.org/pdf/1911.09070.pdf" rel="nofollow noreferrer">EfficientDet</a>. Implementations for both of them can be found over a variety of frameworks.</p>
Object detection+tracking
<p>I am new in the field of CV and trying to build an object detection with yolo and object tracking with DeepSort.
I have some problems with the identification of objects in the video. Here an example:
The sport ball is identified in the video but when it is too close to the person, the detector can not identify it.</p>
<p>In this picture the Ball is identified:</p>
<p><a href="https://i.stack.imgur.com/8x1XR.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/8x1XR.png" alt="enter image description here" /></a></p>
<p>Here the bull is not identified:</p>
<p><a href="https://i.stack.imgur.com/BGiE5.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/BGiE5.png" alt="enter image description here" /></a></p>
<p>How can I improve the detection? I am using pre-trained yolov3(which is trained on the coco dataset) and DeepSort.</p>