Facial feature extraction and pose determination

Nikolaidis, A.; Pitas, Ioannis

doi:10.1016/s0031-3203(99)00176-4

Cited by 118 publications

(55 citation statements)

References 13 publications

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“…Other computer-vision techniques that have been applied for recognizing facial motions are important also for full-body gestures, such as Hidden Markov Models, Principal Component Analysis [132], Contour Models [69] Feature Extraction [101], Gabor Filtering [83].…”

Section: Enabling Recognition Technologiesmentioning

confidence: 99%

A model-based approach for gesture interfaces

Spano

2011

Proceedings of the 3rd ACM SIGCHI Symposium on Engineering Interactive Computing Systems

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This one goes out to the one I love "People shouldn't have to read a manual to open a door, even if it is only one word long (push/pull AbstractThe description of a gesture requires temporal analysis of values generated by input sensors, and it does not fit well the observer pattern traditionally used by frameworks to handle the user's input. The current solution is to embed particular gesture-based interactions into frameworks by notifying when a gesture is detected completely. This approach suffers from a lack of flexibility, unless the programmer performs explicit temporal analysis of raw sensors data. This thesis proposes a compositional, declarative meta-model for gestures definition based on Petri Nets. Basic traits are used as building blocks for defining gestures; each one notifies the change of a feature value. A complex gesture is defined by the composition of other sub-gestures using a set of operators. The user interface behaviour can be associated to the recognition of the whole gesture or to any other sub-component, addressing the problem of granularity for the notification of events.The meta-model can be instantiated for different gesture recognition supports and its definition has been validated through a proof of concept library. Sample applications have been developed for supporting multi-touch gestures in iOS and full body gestures with Microsoft Kinect.In addition to the solution for the event granularity problem, this thesis discusses how to separate the definition of the gesture from the user interface behaviour using the proposed compositional approach.The gesture description meta-model has been integrated into MARIA, a model-based user interface description language, extending it with the description of full-body gesture interfaces.

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Section: Enabling Recognition Technologiesmentioning

confidence: 99%

A model-based approach for gesture interfaces

Spano

2011

Proceedings of the 3rd ACM SIGCHI Symposium on Engineering Interactive Computing Systems

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“…Since pupils correspond to darker regions in the images, pupils are easily detected by applying a simple optimal binary thresholding technique (Gonzalez & Woods, 2008). To avoid pupil false detection, each region segmented in the thresholding phase is validated using biometric properties of the eyes and pupils (Nikolaidis & Pitas, 2000). The contour of each pupil's segmented region is also extracted.…”

Section: On the Automatic Implementation Of The Eye Involuntary Reflementioning

confidence: 99%

On the Automatic Implementation of the Eye Involuntary Reflexes Measurements Involved in the Detection of Human Liveness and Impaired Faculties

Meunier¹

2009

Image Processing

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“…Areas pointed out by the integrals formed a good first estimate of where the templates were to be applied. Other researchers found out that more exact results can be obtained by applying the projection analysis on the intensity image, because of the smooth contours of most of the facial features [38,23,45,51,33]. In [38] rubber snake models are applied on the areas where the integral projections point out.…”

Section: Facial Feature Segmentation By Min-max Analysismentioning

confidence: 99%

A modular approach to facial feature segmentation on real sequences

Votsis

Drosopoulos

Kollias

2003

Signal Processing: Image Communication

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In this paper a modular approach of gradual confidence for facial feature extraction over real video frames is presented. The problem is being dealt under general imaging conditions and soft presumptions. The proposed methodology copes with large variations in the appearance of diverse subjects, as well as of the same subject in various instances within real video sequences. Areas of the face that statistically seem to be outstanding form an initial set of regions that are likely to include information about the features of interest. Enhancement of these regions produces closed objects, which reveal-through the use of a fuzzy system-a dominant angle, i.e. the facial rotation angle. The object set is restricted using the dominant angle. An exhaustive search is performed among all candidate objects, matching a pattern that models the relative position of the eyes and the mouth. Labeling of the winner features can be used to evaluate the features extracted and provide feedback in an iterative framework. A subset of the MPEG-4 facial definition or facial animation parameter set can be obtained. This gradual feature revelation is performed under optimization for each step, producing a posteriori knowledge about the face and leading to a step-by-step visualization of the features in search. r

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Facial feature extraction and pose determination

Cited by 118 publications

References 13 publications

A model-based approach for gesture interfaces

A model-based approach for gesture interfaces

On the Automatic Implementation of the Eye Involuntary Reflexes Measurements Involved in the Detection of Human Liveness and Impaired Faculties

A modular approach to facial feature segmentation on real sequences

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