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Informations générales |
| Auteur |
Tavakoli, Hamed Rezazadegan; Moin, M. Shahram; Heikkilä, Janne |
| Publié |
InTech Open Access Publisher, 2013
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| Abstract |
In this paper, we present a tracking technique
utilizing a simple saliency visual descriptor. Initially, we
define a visual descriptor named local similarity pattern
that mimics the famous texture operator local binary
patterns. The key difference is that it assigns each pixel a
code based on the similarity to the neighbouring pixels.
Later, we simplify this descriptor to a local saliency
operator which counts the number of similar pixels in a
neighbourhood. We name this operator local similarity
number (LSN).
We apply the local similarity number operator to measure
the amount of saliency in a target patch and model the
target. The proposed tracking algorithm uses a joint
saliency‐colour histogram to represent the target in a
mean‐shift tracking framework. We will show that the
proposed saliency‐colour target representation
outperforms texture‐colour where texture modelled by
local binary patterns and colour target representation
techniques are used. |
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International Journal of Advanced Robotic Systems
Auteur: 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, [...]
Publié: 2004
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