Multi-Target Multi-Camera Tracking (MTMCT) tracks many people through video taken from several cameras. Person Re-Identification (Re-ID) retrieves from a gallery images of people similar to a person query image. We learn good features for both MTMCT and Re-ID with a convolutional neural network. Our contributions include an adaptive weighted triplet loss for training and a new technique for har...

Dealing with conflicting and target-specific requirements is an important issue in multi-sensor and multi-target tracking. This paper aims to allocate sensing resources among various targets in reaction to individual information requests. The approach proposed is to introduce agents for every relevant target responsible for its tracking. Such agents are expected to bargain with each other for a...

Quantitative analysis of the dynamics of tiny cellular and subcellular structures in time-lapse cell microscopy sequences requires the development of a reliable multi-target tracking method capable of tracking numerous similar targets in the presence of high levels of noise, high target density, maneuvering motion patterns and intricate interactions. The linear Gaussian jump Markov system proba...

We review some advances of the particle filtering (PF) algorithm that have been achieved in the last decade in the context of target tracking, with regard to either a single target or multiple targets in the presence of false or missing data. The first part of our review is on remarkable achievements that have been made for the single-target PF from several aspects including importance proposal...

Multi-target tracking based on on-line boosting is a significant technique in computer vision. However, it is very difficult to select the optimal classifier in on-line learning process since tracking often relies on an assumption that the appearance model of target is fixed. This would directly lead to a decline in the performance of on-line boosting. In this paper, we presents a novel on-line...

The recently developed labeled multi-Bernoulli (LMB) filter uses better approximations in its update step, compared to the unlabeled multi-Bernoulli filters, and more importantly, it provides us with not only the estimates for the number of targets and their states, but also with labels for existing tracks. This paper presents a novel sensor-control method to be used for optimal multi-target tr...

In recent years, significant progress has been made in the multi-target tracking (MTT) of unmanned aerial vehicle (UAV) swarms. Most existing MTT approaches rely on ideal assumption a pre-set target trajectory. However, practice, trajectory moving cannot be known by UAV advance, which poses great challenge for realizing real-time tracking. Meanwhile, state-of-the-art multi-agent value-based met...