Multi-objects recognition for distributed intelligent sensor networks

Haibo He; Sheng Chen; Yuan Cao; Sachi Desai; Myron E. Hohil

doi:10.1117/12.783105

23 April 2008 Multi-objects recognition for distributed intelligent sensor networks

Haibo He, Sheng Chen, Yuan Cao, Sachi Desai, Myron E. Hohil

Proceedings Volume 6963, Unattended Ground, Sea, and Air Sensor Technologies and Applications X; 69630R (2008) https://doi.org/10.1117/12.783105
Event: SPIE Defense and Security Symposium, 2008, Orlando, Florida, United States

Abstract

This paper proposes an innovative approach for multi-objects recognition for homeland security and defense based intelligent sensor networks. Unlike the conventional way of information analysis, data mining in such networks is typically characterized with high information ambiguity/uncertainty, data redundancy, high dimensionality and real-time constrains. Furthermore, since a typical military based network normally includes multiple mobile sensor platforms, ground forces, fortified tanks, combat flights, and other resources, it is critical to develop intelligent data mining approaches to fuse different information resources to understand dynamic environments, to support decision making processes, and finally to achieve the goals. This paper aims to address these issues with a focus on multi-objects recognition. Instead of classifying a single object as in the traditional image classification problems, the proposed method can automatically learn multiple objectives simultaneously. Image segmentation techniques are used to identify the interesting regions in the field, which correspond to multiple objects such as soldiers or tanks. Since different objects will come with different feature sizes, we propose a feature scaling method to represent each object in the same number of dimensions. This is achieved by linear/nonlinear scaling and sampling techniques. Finally, support vector machine (SVM) based learning algorithms are developed to learn and build the associations for different objects, and such knowledge will be adaptively accumulated for objects recognition in the testing stage. We test the effectiveness of proposed method in different simulated military environments.

Citation Download Citation

Haibo He, Sheng Chen, Yuan Cao, Sachi Desai, and Myron E. Hohil "Multi-objects recognition for distributed intelligent sensor networks", Proc. SPIE 6963, Unattended Ground, Sea, and Air Sensor Technologies and Applications X, 69630R (23 April 2008); https://doi.org/10.1117/12.783105

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available