Active-SWIR signatures for long-range night/day human detection and identification

2013 ◽  
Author(s):  
Robert B. Martin ◽  
Mikhail Sluch ◽  
Kristopher M. Kafka ◽  
Robert Ice ◽  
Brian E. Lemoff
Keyword(s):  
Long Range ◽  
Human Detection ◽  
Detection And Identification

POSE ROBUST HUMAN DETECTION IN DEPTH IMAGES USING MULTIPLY-ORIENTED 2D ELLIPTICAL FILTERS

2010 ◽  
Vol 24 (05) ◽  
pp. 691-717 ◽  
Author(s):  
SANG-HO CHO ◽  
TAEWAN KIM ◽  
DAIJIN KIM
Keyword(s):  
Human Identification ◽  
Human Detection ◽  
Stereo Images ◽  
Bhattacharyya Distance ◽  
Identification Method ◽  
Depth Images ◽  
Detection And Identification ◽  
The Face ◽  
Human Pose ◽  
Spatial Depth

This paper proposes a pose robust human detection and identification method for sequences of stereo images using multiply-oriented 2D elliptical filters (MO2DEFs), which can detect and identify humans regardless of scale and pose. Four 2D elliptical filters with specific orientations are applied to a 2D spatial-depth histogram, and threshold values are used to detect humans. The human pose is then determined by finding the filter whose convolution result was maximal. Candidates are verified by either detecting the face or matching head-shoulder shapes. Human identification employs the human detection method for a sequence of input stereo images and identifies them as a registered human or a new human using the Bhattacharyya distance of the color histogram. Experimental results show that (1) the accuracy of pose angle estimation is about 88%, (2) human detection using the proposed method outperforms that of using the existing Object Oriented Scale Adaptive Filter (OOSAF) by 15–20%, especially in the case of posed humans, and (3) the human identification method has a nearly perfect accuracy.

Long-range detection and identification of underwater mines using very low frequencies (1 to 10 kHz)

1998 ◽  
Author(s):  
Timothy J. Yoder ◽  
Joseph A. Bucaro ◽  
Brian H. Houston ◽  
Harry J. Simpson
Keyword(s):  
Long Range ◽  
Low Frequencies ◽  
Detection And Identification

ROBUST HUMAN DETECTION AND IDENTIFICATION BY USING STEREO AND THERMAL IMAGES IN HUMAN ROBOT INTERACTION

2007 ◽  
Vol 04 (02) ◽  
pp. 161-183 ◽  
Author(s):  
F. GUAN ◽  
L. Y. LI ◽  
S. S. GE ◽  
A. P. LOH
Keyword(s):  
Vision System ◽  
Effective Interaction ◽  
Human Robot Interaction ◽  
Human Detection ◽  
Human Beings ◽  
Robot Interaction ◽  
Thermal Images ◽  
Detection And Identification ◽  
Infrared Thermal Images ◽  
Socially Interactive Robots

In this paper, robust human detection is investigated by fusing the stereo and infrared thermal images for effective interaction between humans and socially interactive robots. A scale-adaptive filter is first designed for the stereo vision system to detect human candidates. To eliminate the difficulty of the vision system in distinguishing human beings from human-like objects, the infrared thermal image is used to solve the ambiguity and reduce the illumination effect. Experimental results show that the fusion of these two types of images gives an improved vision system for robust human detection and identification, which is the most important and essential component of human robot interaction.

Human Detection and Identification by Robots Using Thermal and Visual Information in Domestic Environments

2011 ◽  
Vol 66 (1-2) ◽  
pp. 223-243 ◽  
Author(s):  
Mauricio Correa ◽  
Gabriel Hermosilla ◽  
Rodrigo Verschae ◽  
Javier Ruiz-del-Solar
Keyword(s):  
Visual Information ◽  
Human Detection ◽  
Detection And Identification ◽  
Domestic Environments

Identification of hepatitis a virus in cell cultures by solid phase immune electron microscopy

1986 ◽  
Vol 44 ◽  
pp. 238-239
Author(s):  
C.D. Humphrey ◽  
T.L. Cromeans ◽  
E.H. Cook ◽  
D.W. Bradley
Keyword(s):  
Electron Microscopy ◽  
Liquid Phase ◽  
Cell Cultures ◽  
Rapid Detection ◽  
Hepatitis A ◽  
Hepatitis A Virus ◽  
Solid Phase ◽  
Immune Electron Microscopy ◽  
Detection And Identification

There is a variety of methods available for the rapid detection and identification of viruses by electron microscopy as described in several reviews. The predominant techniques are classified as direct electron microscopy (DEM), immune electron microscopy (IEM), liquid phase immune electron microscopy (LPIEM) and solid phase immune electron microscopy (SPIEM). Each technique has inherent strengths and weaknesses. However, in recent years, the most progress for identifying viruses has been realized by the utilization of SPIEM.

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