Multiple Object Tracking

Multi-Object Tracking (MOT) is the task of detecting the presence of multiple objects in video and associating these detections over time according to object identities. The MOT task is one of the key pillars of computer vision research and is essential for many scene understanding tasks such as surveillance, robotics…

What is Object Tracking? Object Tracking is a method to track detected objects throughout the frames using their spatial and temporal features. What we do in tracking is that, we get the initial set of detections, in the next step we assign them unique id’s and then tracking them throughout…

‍AI-based video analytics is increasingly discussed in the video surveillance industry. But in a broader context, AI will become the subject of precise solution creation in the near future. This implementation is increasingly starting to concern video editing softwares, and companies must choose the best way to optimize this use…

An overview of the challenges and techniques for object tracking — What is Object Tracking? Object Tracking is a technique in which the algorithm tracks the object(s) of interest in a sequence of images or a video. Usually, it involves: Indentifying the object of interest (object detection), usually by generating a bounding box around the object and assigning a unique ID for it Tracking the…

SORT (Simple, Online, and Realtime Tracking) is a well-known, frequently used MOT (multi-object tracker) algorithm that fits well when the objects are not occluded by obstacles or overlapped by each other. There are many such cases, e.g., a factory line with parts moving on the conveyor. …

Feature-based trackers are very often met in the deep-learning industry. Well-known feature-learning DNN models like OSNet generate homogenous re-identification (Re-ID) vectors. Those vectors can be estimated with distance metrics like Euclidean, Cosine, or another. The feature vectors inferred for a single object generate distance results that lay close. Unlike the…

Learn about the current SOTA like ByteTrack, DeepSORT, StrongSORT and OC-SORT First, an introduction will be made to the key metrics used in literature to compare different trackers; after this introduction, a discussion on the SOTA algorithms of object tracking will be conducted. Object detection tries to answer the question…

There are multiple state-of-the-art approaches for object detection [1] [2]. These approaches addresses the perception problem: How do we perceive various objects in the environment? These objects may move or the perceiver may move around relative to the objects in the real-world. Being able to track these objects reliably over…