Human activity recognition using multisensor data fusion based on Reservoir Computing

Model Based Fusion for Multisensor Target Recognition

A multisensor feature-based fusion approach to target recognition using a framework of model-theory is proposed. The Best Discrimination Basis Algorithm (BDBA) based on the best basis selection technique and the Sensory Data Fusion System (SDFS) based on logical models and theories are applied for feature extraction. The BDBA selects the most discriminant basis. The SDFS rst selects features, w...

A New Method for Multisensor Data Fusion Based on Wavelet Transform in a Chemical Plant

This paper presents a new multi-sensor data fusion method based on the combination of wavelet transform (WT) and extended Kalman filter (EKF). Input data are first filtered by a wavelet transform via Daubechies wavelet “db4” functions and the filtered data are then fused based on variance weights in terms of minimum mean square error. The fused data are finally treated by extended Kalman filter...

Multisensor data fusion using fuzzy concepts

In this study, a fuzzy-based multisensor data fusion classifier is developed and applied to land cover classification using ERS-1/JERS-1 SAR composites. This classifier aims at the integration of multisensor and contextual information in a single and a homogeneous framework. Initial Fuzzy Membership Maps (FMM) to different thematic classes are first calculated using classes and sensors a priori...

Multisensor Data Fusion

Classification Accuracy Increase Using Multisensor Data Fusion

The practical use of very high resolution visible and near-infrared (VNIR) data is still growing (IKONOS, Quickbird, GeoEye-1, etc.) but for classification purposes the number of bands is limited in comparison to full spectral imaging. These limitations may lead to the confusion of materials such as different roofs, pavements, roads, etc. and therefore may provide wrong interpretation and use o...