Extracting meaningful information from video sequences for intelligent searches.

Video and image data are knowledge-rich sources of information, but their utility for current and future systems is limited without autonomous methods for understanding and characterizing their content. Semantic-based video understanding may benefit systems dedicated to the detection of insiders, alarm patterns, unauthorized activities in material monitoring applications, etc. A direct benefit of this technology is not only intelligent alarm analysis, but the ability to browse and perform query-based searches for useful and interesting information after video data has been acquired and stored. These searches can provide a tremendous benefit for use in intelligence agency, government, military, and DOE site investigations. This report provides an initial investigation into the algorithms and methods needed to characterize and understand video content. Such algorithms include background modeling, detecting dynamic image regions, grouping dynamic pixels into coherent objects, and robust tracking strategies. With solid approaches for addressing these problems, analysis can be performed seeking to recognize distinctive objects and their motions leading to semantic-based video searches

A fast multi-modal approach to facial feature detection

As interest in 3D face recognition increases the importance of the initial alignment problem does as well. In this paper we present a method utilizing the registered 2D color and range image of a face to automatically identify the eyes, nose, and mouth. These features are important to initially align faces in both standard 2D and 3D face recognition algorithms. For our algorithm to run as fast as possible, we focus on the 2D color information. This allows the algorithm to run in approximately 4 seconds on a 640X480 image with registered range data. On a database of 1,500 images the algorithm achieved a facial feature detection rate of 99.6 % with 0.4 % of the images skippe

Conceptual understanding of screen media parenting: report of a working group

Screen media (television, computers, and videogames) use has been linked to multiple child outcomes, including obesity. Parents can be an important influence on children’s screen use. There has been an increase in the number of instruments available to assess parenting in feeding and physical activity contexts, however few measures are available to assess parenting practices regarding children’s screen media use. A working group of screen media and parenting researchers convened at the preconference workshop to the 2012 International Society for Behavioral Nutrition and Physical Activity (ISBNPA) annual meeting, ‘‘Parenting Measurement: Current Status and Consensus Reports,’’ to identify and prioritize issues in assessing screen media parenting practices. The group identified that screen media use can pose different risks for children, depending on their age and developmental stage, across physiologic, psychosocial, and development outcomes. With that in mind, a conceptual framework of how parents may influence their child’s screen-viewing behaviors was proposed to include the screen media content, context of viewing, and amount viewed. A research agenda was proposed to prioritize a validation of the framework and enhance the ability of researchers to best assess parenting influences across the three domains of content, context and amount of children’s screen media use