Fast, Reliable Head Tracking under Varying Illumination: An Approach Based on Registration of Texture-Mapped 3D Models

By Marco La Cascia, Stan Sclaroff, Vassilis Athitsos. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000

648 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/436ad5af721c56b714b13d68a45ab8898d75514f

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In Aerospace Engineering

In Computer Vision and Pattern Recognition

Citations in the corpus

OpenFace: An open source facial behavior analysis toolkit (2016, methodology): “To measure OpenFace performance on a head pose estimation task we used three publicly available datasets with existing ground truth head pose data: BU [15], Biwi [21] and ICT-3DHP [9].”
3D Constrained Local Model for rigid and non-rigid facial tracking (2012, methodology): “We evaluate our approaches on four publicly available datasets: the Binghamton University 3D dynamic facial expression database (BU-4DFE) [30], the Biwi Kinect head pose database (Biwi) [14], the Boston University head pose database (BU) [6], and our new dataset ICT-3DHP.”
Head Pose Estimation in Computer Vision: A Survey (2009, positive): “The methods that track the head in video sequences using flexible models and tracking methods [14], [81], [82], [94], [124], [140], [147] report a significantly lower error than systems that estimate pose in individual images.”
OpenFace 2.0: Facial Behavior Analysis Toolkit (2018, background): “truth head pose data: BU [16] and ICT-3DHP [10].”
Face tracking and recognition with visual constraints in real-world videos (2008, background): “Numerous approaches to target modeling have attempted to tackle these issues using view-based appearance models [4], contour models [9], 3D models [11], mixture models [10], and kernel representations [6, 8], among others.”
Stable real-time 3D tracking using online and offline information (2004, neutral): “1.”
Lucas-Kanade 20 Years On: A Unifying Framework (2004, neutral): “Other approaches consist of assuming that linear relationship is constant and: (1) using linear regression to find the coefficients (Cootes et al., 1998) and (2) numerically estimating the coefficients using a “difference decomposition” (Gleicher, 1997; Sclaroff and Isidoro, 1998; La Cascia et al.,”
Real-Time Inference of Complex Mental States from Facial Expressions and Head Gestures (2004, methodology): “A more accurate, but computationally intensive approach involves tracking the entire head region using a 3D head model [10, 17, 41].”