Collaborative human tracking with local features in the surveillant camera networks

2011 ◽  
Author(s):  
Yi Zhou ◽  
H. Snoussi ◽  
Shibao Zheng
Keyword(s):  
Local Features ◽  
Camera Networks ◽  
Human Tracking

Visual Human Tracking in Wireless Cameras Networks A SURF-Based Approach

2011 ◽  
pp. 160-175
Author(s):  
Yi Zhou ◽  
Hichem Snoussi ◽  
Shibao Zheng ◽  
Fethi Smach
Keyword(s):  
Visual Tracking ◽  
Local Features ◽  
Camera Networks ◽  
Time Constraints ◽  
Human Tracking ◽  
Interest Point ◽  
Feature Descriptors ◽  
Wireless Camera Networks ◽  
Spatial Coordinates ◽  
Point Detection

In wireless camera networks, the communication load between cameras is a major concern for visual tracking. To save the bandwidth, traditional applications transfer the spatial coordinates under the precondition of camera calibration, which is computationally unreasonable for large and mobile camera networks. In this chapter, we exploit the use of distinctive and fast to compute local features to represent the non-rigid targets. Transmission of feature descriptors between cameras is done without any calibration. Combining the haar-like patterns and relative color information, our local features succeed to re-identify and relocate the target among the distributed cameras. Furthermore, efficient interest point detection and matching scheme are proposed for the visual tracking under real-time constraints.

Consistent Human Tracking Over Self-organized and Scalable Multiple-camera Networks

2014 ◽  
pp. 189-209 ◽  
Author(s):  
Kuan-Hui Lee ◽  
Chun-Te Chu ◽  
Younggun Lee ◽  
Zhijun Fang ◽  
Jenq-Neng Hwang
Keyword(s):  
Camera Networks ◽  
Human Tracking ◽  
Multiple Camera ◽  
Self Organized

A Novel Approach of Human Tracking Mechanism in Wireless Camera Networks

2017 ◽  
pp. 297-323
Author(s):  
Usha Devi Gandhi
Keyword(s):  
Cluster Size ◽  
Cluster Head ◽  
Head Rotation ◽  
Camera Networks ◽  
Human Tracking ◽  
Computational Burden ◽  
Novel Approach ◽  
Wireless Camera Networks ◽  
Mean Time ◽  
Cluster Head Rotation

The sensing power of traditional camera networks for efficiently addressing the critical tasks in the process of cluster – based target tracking of human, such as measurement integration, inclusion/exclusion in the cluster and cluster head rotation. The Wireless Camera Networks efficiently uses distribution friendly representation and methods in which every node contributes to the computation in each mechanism without the requirement of any prior knowledge of the rest of the nodes. These mechanisms and methods are integrated in two different distributed schemas so that it can be implemented in the same mean time without taking into the consideration of cluster size. Thus, the experimental evaluation shows that the proposed schemes and mechanisms drastically reduce the energy consumption and computational burden with respect to the existing methodology.

A privacy-preserving human tracking scheme in centralized cloud based camera networks

2014 ◽  
Author(s):  
Yu-Chi Chen ◽  
Chun-Te Chu ◽  
Jenq-Neng Hwang ◽  
Jang-Hee Yoo
Keyword(s):  
Privacy Preserving ◽  
Camera Networks ◽  
Human Tracking

scholarly journals Human tracking over camera networks: a review

2017 ◽  
Vol 2017 (1) ◽  
Author(s):  
Li Hou ◽  
Wanggen Wan ◽  
Jenq-Neng Hwang ◽  
Rizwan Muhammad ◽  
Mingyang Yang ◽  
...  
Keyword(s):  
Camera Networks ◽  
Human Tracking

Usefulness of Transinformation as a Measure of Human Tracking Performance

1966 ◽  
Author(s):  
T. Wempe ◽  
D. Baty
Keyword(s):  
Tracking Performance ◽  
Human Tracking

Human Tracking in Crowded Scenes Using Integration of Three Kinds of Models and Adaptive Learning

2017 ◽  
Vol 137 (9) ◽  
pp. 1258-1265
Author(s):  
Hiromasa Takada ◽  
Kazuhiro Hotta
Keyword(s):  
Adaptive Learning ◽  
Human Tracking ◽  
Crowded Scenes
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