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Shihong Lao
Researcher at Omron
Publications - 115
Citations - 6152
Shihong Lao is an academic researcher from Omron. The author has contributed to research in topics: Facial recognition system & Object detection. The author has an hindex of 34, co-authored 115 publications receiving 5751 citations. Previous affiliations of Shihong Lao include Tsinghua University.
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Proceedings ArticleDOI
Eyeblink-based Anti-Spoofing in Face Recognition from a Generic Webcamera
TL;DR: A real-time liveness detection approach against photograph spoofing in face recognition, by recognizing spontaneous eyeblinks, which is a non-intrusive manner, which outperforms the cascaded Adaboost and HMM in task of eyeblink detection.
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Multi-View Discriminant Analysis
TL;DR: This work proposes a Multi-view Discriminant Analysis (MvDA) approach, which seeks for a single discriminant common space for multiple views in a non-pairwise manner by jointly learning multiple view-specific linear transforms.
Proceedings ArticleDOI
Fast rotation invariant multi-view face detection based on real Adaboost
TL;DR: A rotation invariant multi-view face detection method based on Real Adaboost algorithm is proposed and a pose estimation method is introduced and results in a processing speed of four frames per second on 320/spl times/240 sized image.
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High-Performance Rotation Invariant Multiview Face Detection
TL;DR: A series of innovative methods are proposed to construct a high-performance rotation invariant multiview face detector, including the width-first-search (WFS) tree detector structure, the vector boosting algorithm for learning vector-output strong classifiers, the domain-partition-based weak learning method, the sparse feature in granular space, and the heuristic search for sparse feature selection.
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Tracking in Low Frame Rate Video: A Cascade Particle Filter with Discriminative Observers of Different Life Spans
TL;DR: Experiments show significantly improved accuracy of the proposed approach in comparison with existing tracking methods, under the condition of low frame rate data and abrupt motion of both target and camera.