In this paper, we introduce a new method for tracking multiple objects. The method combines Kalman filtering and the Expectation Maximization (EM) algorithm ...

The method combines Kalman filtering and the Expectation Maximization (EM) algorithm in a novel way to deal with observations that obey a Gaussian mixture ...

Jan 16, 2023 · What you are looking for is a tracking algorithm that takes motion and appearance into consideration in the association process.

This example shows how to perform automatic detection and motion-based tracking of moving objects in a video from a stationary camera.

We proposed a multiple object tracking algorithm based on Boosted Efficient Binary Local Image Descriptor feature.

Jul 4, 2024 · Our approach addresses two primary challenges: firstly, the binary mask only provides two classes (object and background), unlike the SegPGD ...

Computing the binary mask using spatial correlation is simple and computational efficient because there are only two steps to achieve the goal: edge detection ...

Feb 27, 2023 · The way to turn an object detector into an instance segmentation model is to add a mask prediction branch to the network.

Recently, Multiple Object Tracking has achieved great success, which consists of object detection, feature embed- ding, and identity association.

Multiple object tracking is a broadly used task in multi- ple applications, all the way from bioengineering to security applications.