Correlated Active Appearance Models

Tiddeman, Bernard; Chen, Jingying

doi:10.1109/sitis.2007.92

Cited by 1 publication

(2 citation statements)

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“…Optimisation techniques based on off-the-shelf non-linear optimisers like those described above are typically slow to converge. We compare optimisation using Powell's method with a direct method for optimising the global NCC using an estimate of the Jacobean and Hessian matrices and solving a linear system and a quadratic equation (Tiddeman and Chen, 2007).…”

Section: Shape Update Methodsmentioning

confidence: 99%

“…We use 8 sequences comprising over 500 images in the experiment. Both algorithms are applied to the same set of face sequences using the FastNCC algorithm (Tiddeman and Chen, 2007), Gauss-Newton algorithm (Hager and Belhumeur, 1998), (Matthews and Baker, 2004), Powell's method (Press. et al, 2007) as the Figure 9: Each row consists of a set of selected frames from a tracking sequence with the synthetic texture patches drawn on which indicates the location of the features.…”

Section: Synthetic Data Experimentsmentioning

confidence: 99%

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Face Detection and Tracking With 3d Pga CLM

Meng¹,

Tiddeman²

2010

Proceedings of the International Conference on Computer Vision Theory and Applications

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In this paper we describe a system for facial feature detection and tracking using a 3D extension of the Constrained Local Model (CLM) (Cristinacce and Cootes, 2006) algorithm. The use of a 3D shape model allows improved tracking through large head rotations. CLM uses a shape and texture appearance model to generate a set of region template detectors. A search is then performed in the global pose / shape space using these detectors. The proposed extension uses multiple appearance models from different viewpoints and a single 3D shape model built using Principal Geodesic Analysis (PGA) (Fletcher et al., 2004) instead of direct Principal Components Analysis (PCA). During fitting or tracking the current estimate of pose is used to select the appropriate appearance model. We demonstrate our results by fitting the model to image sequences with large head rotations. The results show that the proposed multi-view 3D CLM algorithm using PGA improves the performance of the algorithm using PCA for tracking faces in videos with large out-of-plane head rotations.Peer reviewe

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Section: Shape Update Methodsmentioning

confidence: 99%