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Face detection is an important component for mobile robots to interact with humans in a natural way. Various face detection algorithms for mobile robots have been proposed; however, almost all of them have not yet met the requirements of the accuracy and the speed to run in real time on a robot platform. In this paper, we present a method of combining color(More)
Detecting and tracking humans are key problems for human-robot interaction. In this paper we present an algorithm for mobile robots to detect and track people reliably, even when humans go through different illumination conditions, often change in a wide variety of poses, and are frequently occluded. We have improved the performance of face and upper body(More)
The ability to recognize faces is a crucial element for human-robot interaction. In this paper, we present an algorithm for mobile robots to detect, track and recognize human faces accurately, even when humans go through different illumination conditions. We track faces using a tracker that combines the algorithm of an adaptive correlation filter with a(More)
Superpixels aim to group homogenous pixels by a series of characteristics in an image. They decimate redundancy that may be utilized later by more computationally expensive algorithms. The most popular algorithms obtain superpixels based on an energy function on a graph. However, these graph-based methods have a high computational time consumption. This(More)
In this paper, we present a real time algorithm for mobile robots to track human faces and estimate face poses accurately, even when humans move freely and far away from the camera or go through different illumination conditions in uncontrolled environments. We combine the algorithm of an adaptive correlation filter with a Viola-Jones object detection to(More)
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