Occluded Pedestrian Tracking using Collaboration of Kalman Filter and Particle Filter
碩士 === 國立臺北大學 === 通訊工程研究所 === 98 === Object tracking is a one of the key feature in intelligent video surveillance. It is a challenging task in tracking algorithm due to the frequent occlusion encountered between moving objects. We propose a novel method to address the problem of tracking and evalu...
Main Authors: | Yen-Hsiang Chang, 張雁翔 |
---|---|
Other Authors: | Daw-Tung Lin |
Format: | Others |
Language: | en_US |
Published: |
2010
|
Online Access: | http://ndltd.ncl.edu.tw/handle/79092032066548672333 |
Similar Items
-
Pedestrian Flow Tracking and Statistics of Monocular Camera Based on Convolutional Neural Network and Kalman Filter
by: Miao He, et al.
Published: (2019-04-01) -
Analyzing Real-Life Pedestrian Measurements Using Kalman Filters
by: Mahakian, David R.
Published: (2019) -
EFFICIENCY ANALYSIS OF EXTENDED KALMAN FILTERING, UNSCENTED KALMAN FILTERING AND UNSCENTED PARTICLE FILTERING
by: I. A. Kudryavtseva
Published: (2016-12-01) -
Pedestrian Tracking Using Interacting Multiple Model Particle Filter for Partial Occlusion
by: Zhen-Chang Chen, et al.
Published: (2017) -
APPLICATION OF MODIFIED UNSCENTED KALMAN FILTER AND UNSCENTED PARTICLE FILTER TO SOLVING TRACKING PROBLEMS
by: I. A. Kudryavtseva, et al.
Published: (2018-04-01)