Multiple targets tracking is a challenging problem due to occlusions or identity switching.
Although the use of prior information about the motion of the targets improves the tracking …

Pedestrian tracking is a key building block in many emerging technologies, and there are
many applications that require a very accurate and reliable pedestrian tracking. Two …

针对粒子滤波中粒子匮乏及样本聚集问题, 提出一种基于佳点集的拟蒙特卡洛粒子滤波算法(
GPS-QMCPF). 该算法利用数论中的佳点集理论和方法来构造出一种新的拟蒙特卡洛序列 …

We propose visual tracking over multiple temporal scales to handle occlusion and non-
constant target motion. This is achieved by learning motion models from the target history at …

This article describes an original strategy for enhancing current state-of-the-art trackers
through the use of motion priors, built as data-driven probabilistic motion models for moving …

We propose a methodology for learning and using a multiple-goal probabilistic motion
model within a particle filter-based target tracking on video streams. In a set of training video …

In this paper, the problem of automated scene understanding by tracking and predicting
paths for multiple humans is tackled, with a new methodology using data from a single, fixed …

We propose a new tracking method capable of handling occlusions and non-constant target
motion. This is achieved using multiple simple motion models, learned at different temporal …

This paper presents a method for learning and predicting human motion in closed
environments. Many surveillance, security, entertainment and smart-home systems require …

People tracking is a key building block in many applications such as abnormal activity
detection, gesture recognition, and elderly persons monitoring. Video-based systems have …