Moving object recognition in eigenspace representation: gait analysis and lip reading

Temporal motion models for monocular and multiview 3D human body tracking

“…Given the high-dimensionality of the data it is natural to look for low-dimensional embeddings of the data (e.g., [30]). To learn pose models a key problem concerns the highly nonlinear space of human poses.…”

Deformable templates for tracking and analysis of intravascular ultrasound sequences

“…We address this question by using Principal Component Analysis (PCA) [8]. This method has been successfully applied to design deformable models [3], [4], [2] to learn and matching image models [21] and sequences [16], [22] and, finally, to represent primitive shapes [32]. …”

Active Shape Model-Based Gait Recognition Using Infrared Images

“…Moving Shape Model spatiotemporal pattern [6]; Principal Components Analysis(PCA) [7] shape of motion [17]; PCA + Canonical Analysis [18] single oscillator [31] Since 2001…”