Congratulations to Darryl D'Souza, CECS Graduate student and his mentor, Dr. Roman Yampolskiy on placing first in Computer and Information Sciences during the 2010 Graduate Research Competition Awards!

Title: Face Detection Analysis using Extended Haar-Like Features

Abstract:
Violaet al. have introduced a rapid object detection scheme based on a boostedcascade of simple features. Lienhart & Maydt have introduced a novel set ofrotated Haar-like features, which significantly enrich this basic set of simpleHaar-like features and which can also be calculated very efficiently. It depicts on average a 10% lower false alarm rate by means of using theseadditional rotated features and overall optimizing the false alarm rate furtherby 12.5% for a given boosted cascade. In this presentation we utilize the Haarcascade, based on this modified scheme. It is used to detect faces in human and avatar upright frontal face datasets.

Goal:
Applying Intel's OpenCV Haar cascade on human and avatar face datasets (complex backgrounds, head rotations,varying illuminations,face occlusions) to obtain accuracies on them and thus evaluate the performance.

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