KEYWORDS: Detection and tracking algorithms, Cameras, Sensors, Control systems, Infrared imaging, Infrared radiation, Camera shutters, Time of flight cameras, Databases, Image processing
Depth images have advantages of simple processing, fog penetration, and little affection by light, thus a body shape detection algorithm based on depth image was proposed to judge personnel evacuation. This study started by making body shape dataset using a depth sensor, then extracting the HOG-depth feature. The best parameters were found, including the range of gradient direction and the number of bins. Next step was to train and classify the body shape dataset using different classifiers, and gentle Adaboost algorithm based on CART weak classifiers got the best result. Then we discussed the effect of traversal method of sliding window, and found a better pixel number of every moving step. At last, the intellectualized control method under actual personnel evacuating situation was completed from the view of software implementation.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.