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Full-Text Articles in Engineering
Feature Pruning For Action Recognition In Complex Environment, Adarsh Nagaraja
Feature Pruning For Action Recognition In Complex Environment, Adarsh Nagaraja
Electronic Theses and Dissertations
A significant number of action recognition research efforts use spatio-temporal interest point detectors for feature extraction. Although the extracted features provide useful information for recognizing actions, a significant number of them contain irrelevant motion and background clutter. In many cases, the extracted features are included as is in the classification pipeline, and sophisticated noise removal techniques are subsequently used to alleviate their effect on classification. We introduce a new action database, created from the Weizmann database, that reveals a significant weakness in systems based on popular cuboid descriptors. Experiments show that introducing complex backgrounds, stationary or dynamic, into the video …
Flexible Computing Architecture For Real Time Skin Detection, Matthew P. Hornung
Flexible Computing Architecture For Real Time Skin Detection, Matthew P. Hornung
Theses and Dissertations
In both the Air Force and Search and Rescue Communities, there is a current need to detect and characterize persons. Existing methods use red-green-blue (RGB) imagery, but produce high false alarm rates. New technology in multi-spectral skin detection is better than the existing RGB methods, but lacks a control and processing architecture to make them efficient for real time problems. We hypothesize that taking a minimalistic approach to the software design, we can perform image preprocessing, feature computation, and skin detection in real time. A number of applications require accurate detection and characterization of persons, human measurement and signature intelligence …
Improved Multispectral Skin Detection And Its Application To Search Space Reduction For Dismount Detection Based On Histograms Of Oriented Gradients, Adam L. Brooks
Theses and Dissertations
Due to the general shift from conventional warfare to terrorism and urban warfare by enemies of the United States in the late 20th Century, locating and tracking individuals of interest have become critically important. Dismount detection and tracking are vital to provide security and intelligence in both combat and homeland defense scenarios including base defense, combat search and rescue (CSAR), and border patrol. This thesis focuses on exploiting recent advances in skin detection research to reliably detect dismounts in a scene. To this end, a signal-plus-noise model is developed to map modeled skin spectra to the imaging response of an …
Modification Of A Modulation Recognition Algorithm To Enable Multi-Carrier Recognition, Angela M. Waters
Modification Of A Modulation Recognition Algorithm To Enable Multi-Carrier Recognition, Angela M. Waters
Theses and Dissertations
Modulation recognition is important for both military and commercial communication applications, particularly in cases where enhanced situation awareness and/or channel assessment is required to mitigate intentional or collateral interference. Modulation recognition via template matching or statistical analysis is a key aspect of non-cooperative (nonmatched filtering) signal interception, classification, and exploitation. This research concerns the evaluation and modification of a conventional Digitally Modulated Signal Recognition Algorithm (DMRA) to enable multi-carrier, Orthogonal Frequency Division Multiplexing (OFDM), waveform recognition. The original DMRA architecture was developed to classify communication signals for three fundamental data modulations, i.e., Amplitude Shift Keying (ASK), Phase Shift Keying (PSK), …
Target Recognition Using Linear Classification Of High Range Resolution Radar Profiles, Ricardo A. Diaz
Target Recognition Using Linear Classification Of High Range Resolution Radar Profiles, Ricardo A. Diaz
Theses and Dissertations
High Range Resolution (HRR) radar profiles map three-dimensional target characteristics onto one-dimensional signals that represent reflected radar intensity along target extent. In this thesis, second through fourth statistical moments are extracted from HRR profiles and input to Fisher Linear Discriminant (FLD) classifiers. An iterative classification process is applied that gradually minimizes required a priori knowledge about the target data. It is found that the second through fourth statistical moments of HRR profiles are useful features in the FLD classification of dissimilar targets and they provide reasonable discrimination of similar targets. Greater than 69% correct classification for two-target scenarios and greater …