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ICETET
2009
IEEE
13 years 5 months ago
Face Description with Local Invariant Features: Application to Face Recognition
A completely automatic face recognition system is presented. The method works on color face images and localizes the face region from them initially. It then determines and select...
Sanjay A. Pardeshi, S. N. Talbar
IJCV
1998
238views more  IJCV 1998»
13 years 7 months ago
Feature Detection with Automatic Scale Selection
The fact that objects in the world appear in different ways depending on the scale of observation has important implications if one aims at describing them. It shows that the not...
Tony Lindeberg
ICASSP
2011
IEEE
12 years 12 months ago
Improving acoustic event detection using generalizable visual features and multi-modality modeling
Acoustic event detection (AED) aims to identify both timestamps and types of multiple events and has been found to be very challenging. The cues for these events often times exist...
Po-Sen Huang, Xiaodan Zhuang, Mark Hasegawa-Johnso...
TCSV
2008
313views more  TCSV 2008»
13 years 8 months ago
Fast Pedestrian Detection Using a Cascade of Boosted Covariance Features
Efficiently and accurately detecting pedestrians plays a very important role in many computer vision applications such as video surveillance and smart cars. In order to find the ri...
Sakrapee Paisitkriangkrai, Chunhua Shen, Jian Zhan...
ICIAR
2010
Springer
14 years 28 days ago
Adaptation of SIFT Features for Robust Face Recognition
Abstract. The Scale Invariant Feature Transform (SIFT) is an algorithm used to detect and describe scale-, translation- and rotation-invariant local features in images. The origina...
Janez Krizaj, Vitomir Struc, Nikola Pavesic