57,170 research outputs found
Dynamic approach for real-time skin detection
Human face and hand detection, recognition
and tracking are important research areas for many computer
interaction applications. Face and hand are considered
as human skin blobs, which fall in a compact region of
colour spaces. Limitations arise from the fact that human
skin has common properties and can be defined in various
colour spaces after applying colour normalization. The
model therefore, has to accept a wide range of colours,
making it more susceptible to noise. We have addressed
this problem and propose that the skin colour could be
defined separately for every person. This is expected to
reduce the errors. To detect human skin colour pixels and
to decrease the number of false alarms, a prior face or hand
detection model has been developed using Haar-like and
AdaBoost technique. To decrease the cost of computational
time, a fast search algorithm for skin detection is proposed.
The level of performance reached in terms of detection
accuracy and processing time allows this approach to be an
adequate choice for real-time skin blob tracking
Multisensor-based human detection and tracking for mobile service robots
The one of fundamental issues for service robots is human-robot interaction. In order to perform such a task and provide the desired services, these robots need to detect and track people in the surroundings. In the present paper, we propose a solution for human tracking with a mobile robot that implements multisensor data fusion techniques. The system utilizes a new algorithm for laser-based legs detection using the on-board LRF. The approach is based on the recognition of typical leg patterns extracted from laser scans, which are shown to be very discriminative also in cluttered environments. These patterns can be used to localize both static and walking persons, even when the robot moves. Furthermore, faces are detected using the robot's camera and the information is fused to the legs position using a sequential implementation of Unscented Kalman Filter. The proposed solution is feasible for service robots with a similar device configuration and has been successfully implemented on two different mobile platforms.
Several experiments illustrate the effectiveness of our approach, showing that robust human tracking can be performed within complex indoor environments
Towards robots reasoning about group behavior of museum visitors: leader detection and group tracking
The final publication is available at IOS Press through http://dx.doi.org/10.3233/AIS-170467Peer ReviewedPostprint (author's final draft
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