Aerospace medicine and biology: A continuing bibliography with indexes (supplement 359)

This bibliography lists 164 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during Jan. 1992. Subject coverage includes: aerospace medicine and physiology, life support systems and man/system technology, protective clothing, exobiology and extraterrestrial life, planetary biology, and flight crew behavior and performance

Robust correlated and individual component analysis

© 1979-2012 IEEE.Recovering correlated and individual components of two, possibly temporally misaligned, sets of data is a fundamental task in disciplines such as image, vision, and behavior computing, with application to problems such as multi-modal fusion (via correlated components), predictive analysis, and clustering (via the individual ones). Here, we study the extraction of correlated and individual components under real-world conditions, namely i) the presence of gross non-Gaussian noise and ii) temporally misaligned data. In this light, we propose a method for the Robust Correlated and Individual Component Analysis (RCICA) of two sets of data in the presence of gross, sparse errors. We furthermore extend RCICA in order to handle temporal incongruities arising in the data. To this end, two suitable optimization problems are solved. The generality of the proposed methods is demonstrated by applying them onto 4 applications, namely i) heterogeneous face recognition, ii) multi-modal feature fusion for human behavior analysis (i.e., audio-visual prediction of interest and conflict), iii) face clustering, and iv) thetemporal alignment of facial expressions. Experimental results on 2 synthetic and 7 real world datasets indicate the robustness and effectiveness of the proposed methodson these application domains, outperforming other state-of-the-art methods in the field

"'Who are you?' - Learning person specific classifiers from video"

We investigate the problem of automatically labelling faces of characters in TV or movie material with their names, using only weak supervision from automaticallyaligned subtitle and script text. Our previous work (Everingham et al. [8]) demonstrated promising results on the task, but the coverage of the method (proportion of video labelled) and generalization was limited by a restriction to frontal faces and nearest neighbour classification. In this paper we build on that method, extending the coverage greatly by the detection and recognition of characters in profile views. In addition, we make the following contributions: (i) seamless tracking, integration and recognition of profile and frontal detections, and (ii) a character specific multiple kernel classifier which is able to learn the features best able to discriminate between the characters. We report results on seven episodes of the TV series “Buffy the Vampire Slayer”, demonstrating significantly increased coverage and performance with respect to previous methods on this material

Mixed Reality Browsers and Pedestrian Navigation in Augmented Cities

International audienceIn this paper, We use a declarative format for positional audio with synchronization between audio chunks using SMIL. This format has been specifically designed for the type of audio used in AR applications. The audio engine associated to this format is running on mobile platforms (iOS, Android). Our MRB browser called IXE use a format based on volunteered geographic information (OpenStreetMap) and OSM documents for IXE can be fully authored in side OSM editors like JOSM. This is in contrast with the other AR browsers like Layar, Juniao, Wikitude, which use a Point of Interest (POI) based format having no notion of ways. This introduces a fundamental difference and in some senses a duality relation between IXE and the other AR browsers. In IXE, Augmented Virtuality (AV) navigation along a route (composed of ways) is central and AR interaction with objects is delegated to associate 3D activities. In AR browsers, navigation along a route is delegated to associated map activities and AR interaction with objects is central. IXE supports multiple tracking technologies and therefore allows both indoor navigation in buildings and outdoor navigation at the level of sidewalks. A first android version of the IXE browser will be released at the end of 2013. Being based on volunteered geographic it will allow building accessible pedestrian networks in augmented cities