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Cited by 12 publications
(15 citation statements)
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References 21 publications
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“…The work in [15] provides a complete survey of the topic, providing full information of the results and categorizing the different available schemes according to the technique used for head pose estimation: appearance template methods [16], detector array methods [17], nonlinear regression methods [18], [19], manifold embedding methods [20], [21], flexible model methods [22], geometric methods [23], tracking methods [24], [25], and hybrid methods [20], [25], [26]. Some of results summarized in [15] are used to compare with this work, as it is depicted in the test section.…”
Section: State Of the Artmentioning
confidence: 99%
“…The work in [15] provides a complete survey of the topic, providing full information of the results and categorizing the different available schemes according to the technique used for head pose estimation: appearance template methods [16], detector array methods [17], nonlinear regression methods [18], [19], manifold embedding methods [20], [21], flexible model methods [22], geometric methods [23], tracking methods [24], [25], and hybrid methods [20], [25], [26]. Some of results summarized in [15] are used to compare with this work, as it is depicted in the test section.…”
Section: State Of the Artmentioning
confidence: 99%
“…However, this approach does not tackle the problem of person dependence. Similarly Yan, et al, [9] and Tofighi, et al, [19] use a linear projection based on Multiclass Linear Discriminant Analysis (M-LDA) instead of a non-linear dimension reduction.…”
Section: Related Workmentioning
confidence: 99%
“…This synchronization step interpolates missing range image samples in a locally linear manner using a simplexization of the subject specific label space. Yan et al, [9] define the k-simplex for an arbitrary sample within the label space as, where is a sample label of subject c, , . .…”
Section: Synchronizationmentioning
confidence: 99%
See 1 more Smart Citation
“…The training stage of the proposed algorithm applies Synchronized Submanifold Embedding (SSE) [21,23]. It uses labeled data to calculate a projection matrix that maps range image samples into a lower dimensional representation.…”
Section: Introductionmentioning
confidence: 99%