A Fast Multi-Modal Approach to Facial Feature Detection

3D Face Recognition: Technology and Applications

“…It is possible to use 3D information in conjunction with 2D for landmark localization [16,24,6]. Although the illumination sensitivity of the 2D features will have a detrimental effect on the joint model, one can use features that are relatively robust to changes in illumination.…”

“…However, for a new setting, these methods are not always applicable. Another typical approach in landmark localization is to detect the easiest landmark first, and to use it in constraining the location of the next landmark [9,16,24]. The problem with these methods is that one erroneously located landmark makes the localization of the next landmark more difficult, if not impossible.…”

“…In [24], 2D Harris corners are used together with 3D shape indices. In some cases 3D is just used to constrain the 2D search [16,6]. Under consistent illumination conditions, 2D is richer in discriminative information, but 3D methods are found to be more robust under changing illumination conditions [81].…”

“…The most frequently used approach to facial landmark detection is to devise a number of heuristics that seem to work for the experimental conditions at hand [9,16,45,53,99,101]. These can be simple rules, such as taking the point closest to the camera as the tip of the nose [24,102], or using contrast differences to detect eye regions [54,102].…”

Multi-attribute robust facial feature localization

“…Recent 3D landmarking studies can be listed as [7], [9], [12]. In addition, multi-modal approaches that combine 2D and 3D data, have shown promising performance [4], [16].…”