• Publications
  • Influence
Multi-PIE
TLDR
This paper introduces the database, describes the recording procedure, and presents results from baseline experiments using PCA and LDA classifiers to highlight similarities and differences between PIE and Multi-PIE.
Imagined Communities: Awareness, Information Sharing, and Privacy on the Facebook
TLDR
It is found that an individual's privacy concerns are only a weak predictor of his membership to the Facebook, and also privacy concerned individuals join the network and reveal great amounts of personal information.
Information revelation and privacy in online social networks
TLDR
This paper analyzes the online behavior of more than 4,000 Carnegie Mellon University students who have joined a popular social networking site catered to colleges and evaluates the amount of information they disclose and study their usage of the site's privacy settings.
The CMU Motion of Body (MoBo) Database
TLDR
The capture setup, the collection procedure and the organization of the database are described, which contains 25 individuals walking on a treadmill in the CMU 3D room.
Silhouette-based human identification from body shape and gait
TLDR
This baseline recognition method provides a lower bound against which to evaluate more complicated procedures and is evaluated on four databases with varying viewing angles, background conditions, walking styles and pixels on target.
Appearance-based face recognition and light-fields
TLDR
A theory of appearance-based object recognition from light-fields is developed, which leads directly to an algorithm for face recognition across pose that uses as many images of the face as are available, from one upwards.
Multi-PIE
An Image Preprocessing Algorithm for Illumination Invariant Face Recognition
TLDR
This work proposes a new image preprocessing algorithm that compensates for illumination variations in images from a single brightness image, which does not require any training steps, knowledge of 3D face models or reflective surface models, and demonstrates large performance improvements.
Integrating Utility into Face De-identification
TLDR
A new algorithm, k-Same-Select, is introduced, which is a formal privacy protection schema based on k-anonymity that provably protects privacy and preserves data utility and empirically validate the findings through evaluations on the FERET database.
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