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General information |
| Author |
Maier, Josef; Humenberger, Martin |
| Published |
InTech Open Access Publisher, 2013
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| Abstract |
In this paper we present a novel computer
vision-based movement detection algorithm which can
be used for applications, such as human detection with
unmanned aerial vehicles. The algorithm uses the
deviation of all pixels from the anticipated geometry
between 2 or more succeeding images to distinguish
between moving and static scenes. This assumption is
valid because only pixels which correspond to moving
objects can violate the epipolar geometry. For the
estimation of the fundamental matrix we present a new
method for rejecting outliers which has, contrary to
RANSAC, a predictable runtime and still delivers reliable
results. To determine movement, especially in difficult
areas, we introduce a novel local adaptive threshold
method, a combined temporal smoothing strategy and
further outlier elimination techniques. All this leads to
promising results where more than 60% of all moving
persons in our own recorded test set have been detected. |
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International Journal of Advanced Robotic Systems
Author: Ottaviano, Erika; Ceccarelli, Marco; Husty, Manfred; Yu, Sung-Hoon; Kim, Yong-Tae; Park, Chang-Woo; Hyun, Chang-Ho; Chen, Xiulong; Feng, Weiming; Sun, Xianyang; Gao, Qing; Grigorescu, Sorin M.; Pozna, Claudiu; Liu, Wanli; Zhankui, Wang; Guo, Meng; Fu, Guoyu; Zhang, Jin; Chen, Wenyuan; Peng, Fengchao; Yang, Pei; Chen, Chunlin; Ding, Rui; Yu, Junzhi; Yang, Qinghai; Tan, Min; Polden, Joseph; Pan, [...]
Published: 2004
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