scholarly journals Contrast invariant features for human detection in far infrared images

2012 ◽  
Author(s):  
Daniel Olmeda ◽  
Arturo de la Escalera ◽  
Jose Maria Armingol
Keyword(s):  
Far Infrared ◽  
Human Detection ◽  
Infrared Images ◽  
Invariant Features

Evidential combination of SVM road obstacle classifiers in visible and far infrared images

2011 ◽  
Author(s):  
Bassem Besbes ◽  
Sonda Ammar ◽  
Yousri Kessentini ◽  
Alexandrina Rogozan ◽  
Abdelaziz Bensrhair
Keyword(s):  
Far Infrared ◽  
Infrared Images

Phase Spread Segmentation of Pedestrians in Far Infrared Images

2011 ◽  
pp. 129-138 ◽  
Author(s):  
Daniel Olmeda ◽  
Arturo de la Escalera ◽  
José Maria Armingol
Keyword(s):  
Far Infrared ◽  
Infrared Images

scholarly journals Pedestrian detection in far infrared images

2013 ◽  
Vol 20 (4) ◽  
pp. 347-360 ◽  
Author(s):  
Daniel Olmeda ◽  
Cristiano Premebida ◽  
Urbano Nunes ◽  
Jose Maria Armingol ◽  
Arturo de la Escalera
Keyword(s):  
Pedestrian Detection ◽  
Far Infrared ◽  
Infrared Images

High-resolution far-infrared images of M83

1989 ◽  
Vol 98 ◽  
pp. 1572 ◽  
Author(s):  
A. P. Marston
Keyword(s):  
High Resolution ◽  
Far Infrared ◽  
Infrared Images

Pedestrian Crowd Detection Based Unmanned Aerial Vehicle Infrared Imagery

2017 ◽  
Vol 873 ◽  
pp. 347-352
Author(s):  
Yong Hao Xiao ◽  
Hong Zhen
Keyword(s):  
Computer Vision ◽  
Support Vector Machine ◽  
Human Detection ◽  
Support Vector ◽  
Infrared Images ◽  
Histogram Of Oriented Gradient ◽  
Detection Approach ◽  
Aerial Vehicle ◽  
Geometric Filtering ◽  
Pedestrian Crowd

Human detection is a keyproblem in computer vision. Recently, some research has been focusing on the detection ofpedestrianusing infrared images. The infrared images have outstanding merit. It depends only on object's temperature, but not on color or texture. In this paper, the pedestrian crowd detection approach is proposed. The approach is compose of ROI blocks extraction and crowd block recognition. ROI blocks can be extracted with circle gradient operator and weighted geometric filtering. Crowd blocks are recognized by support vector machine, which combines histogram of oriented gradient and circle gradient. The experimental results show thatthe approach works effectively in different scenes.

scholarly journals Near-Infrared Images of the Serpens Molecular Cloud Core

1989 ◽  
Vol 120 ◽  
pp. 227-230
Author(s):  
C. Eiroa ◽  
M. Casali
Keyword(s):  
Molecular Cloud ◽  
Large Scale ◽  
Near Infrared ◽  
Far Infrared ◽  
Infrared Images ◽  
Infrared Source ◽  
Stellar Objects ◽  
Dark Clouds ◽  
First Time ◽  
Cloud Core

ABSTRACT:Near-infrared images of the Serpens molecular cloud core have been carried out at UKIRT (Mauna Kea Observatory) using the infrared array camera, IRCAM. A large-scale diffuse nebulosity extending over the central part of the core is observed. Over 100 K-sources are detected in the 30 arc min2 cloud core. Some of them are PMS objects which were previously unknown. For the first time, a near-infrared counterpart of the far-infrared source Seroens FIRS1 has been detected. The 2.2 µm source appears as a point like object at the apex of an extended knotty, jet-like nebulosity oriented towards the northwest. In addition, a group of 11 stellar objects is seen in the position of the IR/radio source SVS4. These objects are embedded in a very faint nebulosity and form one of the densest clustering of young stars found in dark clouds.

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