Documenti accessibili
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Informazioni generali |
| Autore |
Southwell, Benjamin John; Fang, Gu |
| Pubblicato |
InTech Open Access Publisher, 2013
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| edizione |
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| Abstract |
Human object recognition and tracking is
important in robotics and automation. The Kinect sensor
and its SDK have provided a reliable human tracking
solution where a constant line of sight is maintained.
However, if the human object is lost from sight during
the tracking, the existing method cannot recover and
resume tracking the previous object correctly. In this
paper, a human recognition method is developed based
on colour and depth information that is provided from
any RGB‐D sensor. In particular, the method firstly
introduces a mask based on the depth information of the
sensor to segment the shirt from the image (shirt
segmentation); it then extracts the colour information of
the shirt for recognition (shirt recognition). As the shirt
segmentation is only based on depth information, it is
light invariant compared to colour‐based segmentation
methods. The proposed colour recognition method
introduces a confidence‐based ruling method to classify
matches. The proposed shirt segmentation and colour
recognition method is tested using a variety of shirts with
the tracked human at standstill or moving in varying
lighting conditions. Experiments show that the method
can recognize shirts of varying colours and patterns
robustly. |
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International Journal of Advanced Robotic Systems
Autore: 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, [...]
Pubblicato: 2004
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