16142452
Differential video coding of face and gesture events in presentation videos
Currently, bandwidth limitations pose a major challenge for delivering high-quality multimedia information over the Internet to users. In this research, we aim to provide a better compression of presentation videos (e.g., lectures). The approach is based on the idea that people tend to pay more attention to the face and gesturing hands, and therefore these regions are given more resolution than the remaining image. Our method first detects and tracks the face and hand regions using color-based segmentation and Kalman filtering. Next, different classes of natural hand gesture are recognized from the hand trajectories by identifying gesture holds, position/velocity changes, and repetitive movements. The detected face/ hand regions and gesture events in the video are then encoded at higher resolution than the remaining lower-resolution background. We present results of the tracking and gesture recognition approach, and evaluate and compare videos compressed with the proposed method to uniform compression.
9994863
Motion segmentation and pose recognition with motion history gradients
Abstract. This paper presents a fast and simple method using a timed motion history image (tMHI) for representing motion from the gradients in successively layered silhouettes. This representation can be used to (a) determine the current pose of the object and (b) segment and measure the motions induced by the object in a video scene. These segmented regions are not “motion blobs”, but instead are motion regions that are naturally connected to parts of the moving object. This method may be used as a very general gesture recognition “toolbox”. We demonstrate the approach with recognition of waving and overhead clapping motions to control a music synthesis program.
10444578
A reliable-inference framework for recognition of human actions
We present an action recognition method based on the concept of reliable inference. Our approach is formulated in a probabilistic framework using posterior class ratios to verify the saliency of an input before committing to any action classification. The framework is evaluated in the context of walking, running, and standing at multiple viewpoints and compared to ML and MAP approaches. Results examining individual silhouette images with the framework demonstrate that these actions can be reliably discriminated while discounting confusing images.
119007
Categorical representation and recognition of oscillatory motion patterns
Many communicative behaviors in the animal kingdom consist of performing and recognizing specialized patterns of oscillatory motion. Here we present an approach to the representation and recognition of these oscillatory motions based on the categorical organization of a simple sinusoidal model having very specific and limited parameter values. This characterization is used to specify the types and layout of computation for recognizing the patterns. Results of the method are demonstrated with real oscillatory motions showing the viability of a structured categorical framework.
10341811
A Two-Stage Template Approach to Person Detection in Thermal Imagery
We present a two-stage template-based method to detect people in widely varying thermal imagery. The approach initially performs a fast screening procedure using a generalized template to locate potential person locations. Next an AdaBoosted ensemble classifier using automatically tuned filters is employed to test the hypothesized person locations. We demonstrate and evaluate the approach using a challenging dataset of thermal imagery
17800570
A Robust Human-Silhouette Extraction Technique for Interactive Virtual Environments
In this paper, we present a method for robustly extracting the silhouette form of the participant within an interactive environment. The approach overcomes the inherent problems associated with traditional chroma-keying, background subtraction, and rear-light projection methods. We employ a specialized infrared system while not making the underlying technology apparent to those interacting within the environment. The design also enables multiple video projection screens to be placed around the user. As an example use of this technology, we present an interactive virtual aerobics system. Our current implementation is a portable system which can act as a re-usable infrastructure for many interactive projects.
18286129
Workflow Based Just-in-time Training
This paper focuses on the problem of information overload for newcomers in an organisation. We propose to address it by constructing a smart personal training assistant based upon workflow tools to drive temporal management of a just-intime workplace training system which will deliver a personalised and structured presentation of organisational documents.
14742091
On local pruning of association rules using directed hypergraphs
Here we propose an adaptive local pruning method for association rules. Our method exploits the exact mapping between a certain class of association rules, namely those whose consequents are singletons and backward directed hypergraphs (B-graphs). The hypergraph which represents the association rules is called an association rules network(ARN). Here we present a simple example of an ARN. We further prove several properties of the ARN and apply the results of our approach to two popular data sets.
12006498
Computing depth under ambient illumination using multi-shuttered light
Range imaging has become a critical component of many computer vision applications. The quality of the depth data is of critical importance, but so is the need for speed. Shuttered light-pulse (SLP) imaging uses active illumination hardware to provide high quality depth maps at video frame rates. Unfortunately, current analytical models for deriving depth from SLP imagers are specific to the number of shutters and have a number of deficiencies. As a result, depth estimation often suffers from bias due to object reflectivity, incorrect shutter settings, or strong ambient illumination such as that encountered outdoors. These limitations make SLP imaging unsuitable for many applications requiring stable depth readings. This paper introduces a method that is general to any number of shutters. Using three shutters, the new method produces invariant estimates under changes in ambient illumination, producing high quality depth maps in a wider range of situations.
17316572
Aligning Ontologies through Formal Concept Analysis
Abstract.Ontologies have been developed for a number of knowledge domains as di-verseasclinicalterminology,photocamerapartsandmicro-arraygeneexpressiondata.However,aninnatecharacteristicofthedevelopmentofontologiesisthattheyareoftencreatedbyindependentgroupsofexpertise,whichgeneratedthenecessityofmergingandaligningontologiescoveringoverlappingdomains.Manyalgorithmsandtoolshavebeenproposedformergingofontologies,butmostofthemdisregardthestructuralpropertiesofthesourceontologies,focusingmostlyonsyntacticanalysis.This article focuses on an alignment method for ontologies based on Formal ConceptAnalysis,adataanalysistechniquefoundedonlatticetheory. 1 Introduction IntheheartofSemanticWebinitiative,proposedbyTimBerners-lee[2,3],liestheideaofmachineprocessableinformation,suchthatautomatedagents,orsoftbots,couldscanthewebspaceforinformationwithaspeciﬂcmeaning.Nevertheless,theunderstandingofmeaninginWebpagesdesignedforhumansisnotaneasytaskforthepresentgenerationofsoftbotsandontologiescangreatlyassistinthisendeavour.Manyinitiativesaroundtheworldhavecreatedontologies.Someoftheseontologieswerecreatedforhighleveldescriptionoftheworld,whereasothersrepresentveryspeciﬂcsub-jects,likebreastcancer,forinstance.Sometimes,ontologiesdevelopedindependentlymayhavesomeoverlaps.TheforementionedBreastCancerOntology,forexample,mayhavecommonconceptsandrelationswithaGeneOntology.Theseoverlapsareveryimpor-tantfromthepointofviewofinformationintegration,becausethecommonontologicalentitieshavetobeidentiﬂedbeforeinformationcanbesuccessfullyintegrated.Forthisreason,mergeandalignmentofontologieshavereceivedsigniﬂcantattentionfromtheresearchcommunityinthelastsixyears.Theﬂrstimportantissueinmerge/alignmentofontologiesistherelationsymbol-meaning.Ontologiesareconstitutedofsymbols(entities)andrelationsbetweensymbols.However,inSemiotics[18]symbolshaveassociatedmeaning,whichlinksthemtotheirreferent
29147523
SCAPE: shape completion and animation of people
We introduce the SCAPE method (Shape Completion and Animation for PEople)---a data-driven method for building a human shape model that spans variation in both subject shape and pose. The method is based on a representation that incorporates both articulated and non-rigid deformations. We learn a pose deformation model that derives the non-rigid surface deformation as a function of the pose of the articulated skeleton. We also learn a separate model of variation based on body shape. Our two models can be combined to produce 3D surface models with realistic muscle deformation for different people in different poses, when neither appear in the training set. We show how the model can be used for shape completion --- generating a complete surface mesh given a limited set of markers specifying the target shape. We present applications of shape completion to partial view completion and motion capture animation. In particular, our method is capable of constructing a high-quality animated surface model of a moving person, with realistic muscle deformation, using just a single static scan and a marker motion capture sequence of the person.