Many people have confusion about object detection and tracking. Object detection and object tracking are two different terms used in deep learning and measuring object movements. The post is a good read for you, as it has briefly explained each essential point that you should know about them.
What is object tracking?
Object tracking is a software solution integrated with cameras and other tools and starts working with the detection of an object and concludes with the identification of the objects and disclosing of its location in real-time. In simple words, an object tracking system is an application that automatically detects an object from an image or video and tracks the movement with the running images/videos. Just like this, there is a Checkpoint metal detection. It is a security technique used to detect any metal objects that may have been hidden in clothing or other items a person is carrying. It is commonly used at airports, government buildings, and other places where security is important. If you want to get more information go to this site.
What is object detection?
Object detection is a method in which an expert detects a target object from an image or video. It works well when the object is present in the image or video. Further, it doesn’t detect the object if it is hidden due to any reason.
Types of object tracking
There are basically three types of object tracking. The types are as follows:
- Image tracking – It aims to track 2D images of interests based on the produced input. There is tracking of that image with its movement in the setting. Experts use it for datasets with asymmetry, highly contrasting images, and multiple identical differences with the target image and other images. For the detection and augmentation of images, it relies on computer vision.
- Video tracking – Experts use it to track moving objects in a produced live video. Due to this, video tracking is highly reliable. It can process real-time, live, and recorded videos.
- Visual tracking – It is a topic of study in computer vision and experts use it in an extensive array of today’s scenarios. Its primary goal is to predict the future position of a visual target without the presence of images or videos.
Differences between object detection and object tracking
As mentioned above, object detection and object tracking are two different things in computer vision or deep learning. Object tracking relates to a method through which experts predict a target object’s position in a frame of an image or video. On the other hand, object detection is a way to detect the targeted object in a single frame of an image/video. It works when the object is available in the produced input and a part of object tracking.
Object tracking process
The process of object tracking has four stages that are as follows:
- Target initialisation
- Appearance modelling
- Motion estimation
- Target positioning
Object tracking levels
The level of object tracking is of two types that are as follows:
- Single object tracking – It aims to track an object of a single category or class.
- Multiple object tracking – It focuses on tracking multiple objects of several different categories or classes.
Why object tracking
It is highly beneficial in machine learning and deep learning. Some of the benefits of object tracking are as follows:
- It facilitates in establishing the identification of objects across frames
- It producing real-time information based on the location and appearance of objects in the live or recorded videos
- It conducts local searches very fast
Challenges in object tracking
The tracking of objects in a produced input is not as easy as many of you might be thinking. It is full of several challenges that are as follows:
- Occlusion
- Background clutter
- Training and tracking speed
- Varying spatial scales
- Anchor Boxes
- Feature extraction