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首页> 外文期刊>International Journal of Advanced Robotic Systems >Human Object Recognition Using Colour and Depth Information from an RGB-D Kinect Sensor
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Human Object Recognition Using Colour and Depth Information from an RGB-D Kinect Sensor

机译:使用来自RGB-D Kinect传感器的颜色和深度信息进行人体目标识别

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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 recog...
机译:人体目标识别和跟踪在机器人技术和自动化中很重要。 Kinect传感器及其SDK提供了可靠的人工跟踪解决方案,可保持恒定的视线。但是,如果在跟踪过程中看不见人类对象,则现有方法将无法恢复并继续正确地跟踪先前的对象。在本文中,基于任何RGB-D传感器提供的颜色和深度信息,开发了一种人类识别方法。特别地,该方法首先基于传感器的深度信息引入掩模以从图像分割衬衫(衬衫分割);然后提取衬衫的颜色信息以进行识别(衬衫识别)。由于衬衫分割仅基于深度信息,因此与基于颜色的分割方法相比,它是不变的。所提出的颜色识别方法引入了基于置信度的裁定方法来对匹配进行分类。建议的衬衫分割和色彩识别...

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