Results 201 to 210 of about 48,415 (254)

AI-Assisted Vision Alarming System for Blind and Vision- Impaired People. [PDF]

Sensors (Basel)
Tran LC, Ly SK, Blacklidge R, Shemmell J, Difford N, Cox DE, Harada T.   +6 more
europepmc   +1 more source

Enhanced range doppler mapping algorithm for passive GNSS based radar aerial target detection. [PDF]

Sci Rep
Zhang Z, Xiaojing M, Zheng Y, Peng W, Jiaxiang Z.   +4 more
europepmc   +1 more source

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Detecting moving objects

International Journal of Computer Vision, 1990
The detection of moving objects is important in many tasks. This paper examines moving object detection based primarily on optical flow. We conclude that in realistic situations, detection using visual information alone is quite difficult, particularly when the camera may also be moving.
Thompson, W., Pong, Ting Chuen
openaire   +1 more source

Moving object detection by a mounted moving camera

IEEE EUROCON 2015 - International Conference on Computer as a Tool (EUROCON), 2015
Accurate moving object detection is one of the most important topic for surveillance systems. Background subtraction works well for videos acquired by stationary mounted camera. However, it does not work for mounted moving cameras since the background objects also move in two consecutive frames.
Ozge Mercanoglu Sincan, Vahid Babaei Ajabshir, Hacer Yalim Keles, Suleyman Tosun   +3 more
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Detecting moving objects from a moving platform

Proceedings 1992 IEEE International Conference on Robotics and Automation, 2003
The authors present a system that successfully detects edge segments of moving objects viewed by a translating camera. The system uses two key concepts. First, a complex logarithmic mapping (CLM) is used to simplify detection of the desired movement. This converts the problem from one of detecting a complex motion along both the X and Y axes, to one of
J. Frazier, R. Nevatia
openaire   +1 more source

Moving Object's Detect in a Monocular Moving Camera

2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing, 2013
Recently, there has been increasing interest in using mobile robots within spaces where humans reside, and safe navigation by effective sensing becomes an important issue. In this paper, we describe a method to detect moving objects that exist in front of an autonomously navigating robot by analyzing images of a monocular color camera mounted on the ...
Ye-gang Chen, Xiao-rong Diao
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MODA: moving object detecting architecture

IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, 1993
A type of cellular neural network (CNN) is described, which may be classified in the broader category of generalized cellular neural networks (GCNNs). Its novelty consists both in the task it performs and in its architecture and way of operation. The input to the network is a two-dimensional picture that is processed continuously in order to detect ...
CIMAGALLI V., BOBBI M., BALSI, Marco
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Detecting Abandoned Objects With a Moving Camera

IEEE Transactions on Image Processing, 2010
This paper presents a novel framework for detecting nonflat abandoned objects by matching a reference and a target video sequences. The reference video is taken by a moving camera when there is no suspicious object in the scene. The target video is taken by a camera following the same route and may contain extra objects.
Hui Kong 0001, Jean-Yves Audibert, Jean Ponce   +2 more
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Robust Moving Object Detection on Moving Platforms

2006
Most moving object detection methods rely on approaches similar to background subtraction or frame differences that require camera to be fixed at a certain position. However, on mobile robots, a background model can not be maintained because of the camera motion introduced by the robot motion.
Ming-Yu Shih, Bwo-Chau Fu
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A hierarchical method for detection of moving objects

Proceedings of 1st International Conference on Image Processing, 2002
This paper deals with segmentation and estimation of motion for two successive images in a sequence whatever the camera situation is (static or mobile). A hierarchical method is described. The model energy is composed of two main parts, one is defined at pixel scale, and the other one on regions. These two terms are optimized alternatively. >
Wei Xiong, Christine Graffigne
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