Abstract:
In this article we present our software framework for embedded online data fusion, called I-SENSE. We discuss the fusion model and the decision modeling approach using su...Show MoreMetadata
Abstract:
In this article we present our software framework for embedded online data fusion, called I-SENSE. We discuss the fusion model and the decision modeling approach using support vector machines. Due to the system complexity and the genetic approach a data oriented model is introduced. The main focus of the article is targeted at our techniques for extracting features of acoustic-and visual-data. Experimental results of our "traffic surveillance" case study demonstrate the feasibility of our multi-level data fusion approach.
Date of Conference: 05-07 September 2007
Date Added to IEEE Xplore: 07 January 2008
ISBN Information:
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Fusion Approach ,
- Support Vector Machine ,
- Decision Model ,
- Data Fusion ,
- Software Framework ,
- Error Rate ,
- Classification Results ,
- Visual Features ,
- Non-stationary ,
- Radial Basis Function ,
- Time Resources ,
- Types Of Sensors ,
- Acoustic Features ,
- Preferred Characteristics ,
- Memory Resources ,
- Spectral Estimation ,
- Vision Sensors ,
- Histogram Bins ,
- Different Types Of Sensors ,
- Histogram Features ,
- Multi-sensor Fusion ,
- Orientation Histogram ,
- Large Trucks ,
- Cepstral Coefficients ,
- Standard Support Vector Machine ,
- Good Classification Results ,
- Histogram Of Values ,
- System Task ,
- Management Units ,
- Extract Visual Features
Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Fusion Approach ,
- Support Vector Machine ,
- Decision Model ,
- Data Fusion ,
- Software Framework ,
- Error Rate ,
- Classification Results ,
- Visual Features ,
- Non-stationary ,
- Radial Basis Function ,
- Time Resources ,
- Types Of Sensors ,
- Acoustic Features ,
- Preferred Characteristics ,
- Memory Resources ,
- Spectral Estimation ,
- Vision Sensors ,
- Histogram Bins ,
- Different Types Of Sensors ,
- Histogram Features ,
- Multi-sensor Fusion ,
- Orientation Histogram ,
- Large Trucks ,
- Cepstral Coefficients ,
- Standard Support Vector Machine ,
- Good Classification Results ,
- Histogram Of Values ,
- System Task ,
- Management Units ,
- Extract Visual Features