Brunelli, R.,
Falavigna, D.,
Person Identification Using Multiple Cues,
PAMI(17), No. 10, October 1995, pp. 955-966.
IEEE DOI
Template Matching.
Robust Technique. Template matching approach. Combines acoustic and visual features.
BibRef
9510
Brunelli, R.[Roberto],
Falavigna, D.[Daniele],
Poggio, T.[Tomaso],
Stringa, L.[Luigi],
Automatic Person Recognition by Acoustic and Geometric Features,
MVA(8), No. 5, 1995, pp. 317-325.
Springer DOI
BibRef
9500
Brunelli, R.[Roberto],
Falavigna, D.[Daniele],
Poggio, T.[Tomaso],
Stringa, L.[Luigi],
Recognition system, particularly for recognising people,
US_Patent5,412,738, May 2, 1995.
WWW Link.
See also Fondazione Bruno Kessler.
BibRef
9505
Brunelli, R., and
Poggio, T.,
Face Recognition: Features versus Templates,
PAMI(15), No. 10, October 1993, pp. 1042-1052.
IEEE DOI Compares 2 simple techniques, one based on geometric features the
other based on almost-gray-level template matching. 90% using
features and perfect results using template matching.
Using 47 examples.
BibRef
9310
Sung, K.K.[Kah-Kay], and
Poggio, T.[Tomaso],
Example-Based Learning for View-Based Human Face Detection,
PAMI(20), No. 1, January 1998, pp. 39-51.
IEEE DOI
9803
BibRef
Earlier: A2, A1:
ARPA94(II:843-850).
BibRef
And: A1, A2:
MIT AI Memo-1521, January 1995.
View Interpolation.
WWW Link.
BibRef
Sung, K.K.[Kah-Kay],
Poggio, T.[Tomaso],
Learning human face detection in cluttered scenes,
CAIP95(432-439).
Springer DOI
9509
BibRef
Heisele, B.[Bernd],
Serre, T.[Thomas],
Prentice, S.[Sam],
Poggio, T.[Tomaso],
Hierarchical classification and feature reduction for fast face
detection with support vector machines,
PR(36), No. 9, September 2003, pp. 2007-2017.
Elsevier DOI
0307
BibRef
Heisele, B.[Bernd],
Poggio, T.[Tomaso],
Pontil, M.[Massimiliano],
Face Detection in Still Gray Images,
MIT AI Memo-1687, May, 2000.
WWW Link.
0105
BibRef
Serre, T.[Thomas],
Heisele, B.[Bernd],
Mukherjee, S.[Sayan],
Poggio, T.[Tomaso],
Feature Selection for Face Detection,
MIT AI Memo-1697, September, 2000.
Method to select features for a face detection system using
Support Vector Machines (SVMs).
WWW Link.
0105
BibRef
Sinha, P.[Pawan],
Poggio, T.[Tomaso],
View-Based Strategies for 3D Object Recognition,
MIT AI Memo-1518, November 1994.
BibRef
9411
Brunelli, R.,
Poggio, T.,
Face Recognition Through Geometrical Features,
ECCV92(792-800).
Springer DOI
BibRef
9200
Poggio, T.[Tomaso],
Brunelli, R.[Roberto],
A Novel Approach to Graphics,
MIT AI Memo-354, February 1992.
WWW Link.
BibRef
9202
Brunelli, R.,
Poggio, T.,
Hyperbf Networks For Real Object Recognition,
IJCAI91(1278-1284).
BibRef
9100
Beymer, D.J.[David J.],
Poggio, T.[Tomaso],
Face Recognition from One Example View,
ICCV95(500-507).
IEEE DOI
PS File.
BibRef
9500
And:
MIT AI Memo-1536, September, 1995.
PS File. And
WWW Link. Good results from 2-D example views alone.
BibRef
Poggio, T.[Tomaso],
Beymer, D.J.[David J.],
Learning Networks for Face Analysis and Synthesis,
AFGR95(160-165).
PS File.
BibRef
9500
Beymer, D.J.[David J.],
Pose-Invariant Face Recognition Using Real and Virtual Views,
MIT AI-TR-1574, March, 1996.
WWW Link.
BibRef
9603
Beymer, D.J.[David J.],
Face Recognition Under Varying Pose,
CVPR94(756-761).
IEEE DOI
PS File.
BibRef
9400
And:
MIT AI Memo-1461, December 1993.
WWW Link. Or:
PS File. Iconic model 98% for 62 people.
BibRef
Beymer, D.J.[David J.],
Vectorizing Face Images by Interleaving Shape and Texture Computations,
MIT AI Memo-1537, September, 1995.
WWW Link. Or:
PS File.
BibRef
9509
Beymer, D.J.[David J.],
Feature Correspondence by Interleaving Shape and Texture Computations,
CVPR96(921-928).
IEEE DOI
PS File.
BibRef
9600
And:
MIT AI Memo-1537, 1995.
PS File.
BibRef
Poggio, T.[Tomaso],
Beymer, D.J.[David J.],
Shashua, A.[Amnon],
Example-based image analysis and synthesis
using pixelwise correspondence,
US_Patent5,745,668, Apr 28, 1998
WWW Link.
BibRef
9804
Beymer, D.J.[David J.],
Shashua, A.[Amnon], and
Poggio, T.[Tomaso],
Example Based Image Analysis and Synthesis,
MIT AI Memo-1431, November 1993.
WWW Link.
BibRef
9311
Romano, R.,
Beymer, D.J.,
Poggio, T.,
Face Verification for Real-Time Applications,
ARPA96(747-756).
BibRef
9600
Chapter on Face Recognition, Human Pose, Detection, Tracking, Gesture Recognition, Fingerprints, Biometrics continues in
Face Analysis, Shading, Illumination, Lighting and Color Variations .