Three-dimensional object recognition from single two-dimensional images
Artificial Intelligence
Recognition by Linear Combinations of Models
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special issue on interpretation of 3-D scenes—part I
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
Perceptual Organization and Visual Recognition
Perceptual Organization and Visual Recognition
Unsupervised Learning of Models for Recognition
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
Object Classification Using a Fragment-Based Representation
BMVC '00 Proceedings of the First IEEE International Workshop on Biologically Motivated Computer Vision
Acquiring Robust Representations for Recognition from Image Sequences
Proceedings of the 23rd DAGM-Symposium on Pattern Recognition
A direct method for stereo correspondence based on singular value decomposition
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Proceedings of the 4th symposium on Applied perception in graphics and visualization
Psychophysics for perception of (in)determinate art
Proceedings of the 4th symposium on Applied perception in graphics and visualization
Components for face recognition
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
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For humans, faces are highly overlearned stimuli, which are encountered in everyday life in all kinds of poses and views. Using psychophysics we investigated the effects of viewpoint on human face recognition. The experimental paradigm is modeled after the inter-extra-ortho experiment using unfamiliar objects by B眉lthoff and Edelman [5]. Our results show a strong viewpoint effect for face recognition, which replicates the earlier findings and provides important insights into the biological plausibility of view-based recognition approaches (alignment of a 3D model, linear combination of 2D views and view-interpolation). We then compared human recognition performance to a novel computational view-based approach [29] and discuss improvements of view-based algorithms using local part-based information.