The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper aims to answer the following questions: 1) How to detect and predict a bed-exit movement, and 2) How early a bed-exit movement can be predicted before it actually occurs. To achieve the above goals we consider the following sensing modalities for observing the human motion during a bed-exit: RGB images, depth images and radio frequency (RF) sensing. Using the measurements from the aforementioned...
In this paper, an image-based method is presented for fall detection using statistical human posture sequence modeling. Specifically, a series of laboratory simulated falls and activities of daily living (ADLs) are performed and recorded by a Kinect sensor as training video data. The skeleton view of a human body in these video recordings is extracted using the Kinect for Windows SDK. Hidden Markov...
This paper presents a novel approach for combining a set of registered images into a composite mosaic with no visible seams and minimal texture distortion. To promote execution speed in building large area mosaics, the mosaic space is divided into disjoint regions of image intersection based on a geometric criterion. Pair-wise image blending is performed independently in each region by means of watershed...
We present an automatic disparity-based approach for 3D face modeling, from two frontal and one profile view stereo images, for 3D face recognition applications. Once the images are captured, the algorithm starts by extracting selected 2D facial features from one of the frontal views and computes a dense disparity map from the two frontal images. We then align a low resolution 2D mesh model to the...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.