Howtosignalprocessing
Object tracking refers to the ability to estimate or predict the position of a target object in each consecutive frame in a video once the initial position of the target object is defined. On the other hand, object detection is the process of detecting a target object in an image or a single frame of the video.
- Can Yolo be used for object tracking?
- Why is object detection and tracking important?
- What is tracking by detection?
- What are the differences between object detection and segmentation?
Can Yolo be used for object tracking?
YOLOv4 — Optimal Speed and Accuracy of Object Detection
This version of YOLO has an Optimal Speed and Accuracy of Object Detection compared to all the previous versions and other state-of-the-art object detectors. The image below shows the YOLOv4 outperforming YOLOv3 and FPS in speed by 10% and 12% respectively.
Why is object detection and tracking important?
Detecting and tracking objects are among the most prevalent and challenging tasks that a surveillance system has to accomplish in order to determine meaningful events and suspicious activities, and automatically annotate and retrieve video content.
What is tracking by detection?
The tracking-by-detection method involves an independent detector that is applied to all image frames to obtain likely detections, and then a tracker, which is run on the set of detections. Hereby, the tracker attempts to perform data association (for example, linking the detections to obtain complete trajectories).
What are the differences between object detection and segmentation?
So, the difference between instance segmentation and object detection techniques is that object detectors only detect objects in images. Conversely, instance segmentation solutions provide a fine-grained understanding of image data by defining and classifying each instance present in visual input.
