• Publications
  • Influence
Eigenfaces for Recognition
A near-real-time computer system that can locate and track a subject's head, and then recognize the person by comparing characteristics of the face to those of known individuals, and that is easy to implement using a neural network architecture. Expand
Face recognition using eigenfaces
  • M. Turk, A. Pentland
  • Computer Science
  • Proceedings. IEEE Computer Society Conference on…
  • 3 June 1991
An approach to the detection and identification of human faces is presented, and a working, near-real-time face recognition system which tracks a subject's head and then recognizes the person byExpand
Pfinder: real-time tracking of the human body
Pfinder uses a multi-class statistical model of color and shape to obtain a 2-D representation of head and hands in a wide range of viewing conditions, useful for applications such as wireless interfaces, video databases, and low-bandwidth coding. Expand
Probabilistic Visual Learning for Object Representation
An unsupervised technique for visual learning is presented, which is based on density estimation in high-dimensional spaces using an eigenspace decomposition and is applied to the probabilistic visual modeling, detection, recognition, and coding of human faces and nonrigid objects. Expand
Pfinder: Real-Time Tracking of the Human Body
Pfinder is a real-time system for tracking people and interpreting their behavior that uses a multiclass statistical model of color and shape to obtain a 2D representation of head and hands in a wide range of viewing conditions. Expand
View-based and modular eigenspaces for face recognition
A modular eigenspace description technique is used which incorporates salient features such as the eyes, nose and mouth, in an eigenfeature layer, which yields higher recognition rates as well as a more robust framework for face recognition. Expand
A Bayesian Computer Vision System for Modeling Human Interactions
A real-time computer vision and machine learning system for modeling and recognizing human behaviors in a visual surveillance task and demonstrates the ability to use these a priori models to accurately classify real human behaviors and interactions with no additional tuning or training. Expand
A New Sense for Depth of Field
  • A. Pentland
  • Computer Science, Geology
  • IEEE Transactions on Pattern Analysis and Machine…
  • 18 August 1985
Experiments with realistic imagery show that measurement of focal gradients resulting from the limited depth of field inherent in most optical systems can provide depth information roughly comparable to stereo disparity or motion parallax, while avoiding image-to-image matching problems. Expand
Real-Time American Sign Language Recognition Using Desk and Wearable Computer Based Video
We present two real-time hidden Markov model-based systems for recognizing sentence-level continuous American sign language (ASL) using a single camera to track the user's unadorned hands. The firstExpand
Fractal-Based Description of Natural Scenes
  • A. Pentland
  • Computer Science, Medicine
  • IEEE Transactions on Pattern Analysis and Machine…
  • 1 November 1984
The3-D fractal model provides a characterization of 3-D surfaces and their images for which the appropriateness of the model is verifiable and this characterization is stable over transformations of scale and linear transforms of intensity. Expand