Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Fu-Jie Huang"'
Publikováno v:
ICDAR
The machine learning and pattern recognition communities are facing two challenges: solving the normalization problem, and solving the deep learning problem. The normalization problem is related to the difficulty of training probabilistic models over
Publikováno v:
CVPR
We present an unsupervised method for learning a hierarchy of sparse feature detectors that are invariant to small shifts and distortions. The resulting feature extractor consists of multiple convolution filters, followed by a feature-pooling layer t
Autor:
Yann LeCun, Fu Jie Huang
Publikováno v:
CVPR (1)
The detection and recognition of generic object categories with invariance to viewpoint, illumination, and clutter requires the combination of a feature extractor and a classifier. We show that architectures such as convolutional networks are good at
Publikováno v:
CVPR (2)
We assess the applicability of several popular learning methods for the problem of recognizing generic visual categories with invariance to pose, lighting, and surrounding clutter. A large dataset comprising stereo image pairs of 50 uniform-colored t
Autor:
Fu Jie Huang, Tsuhan Chen
Publikováno v:
MMSP
In this demo, we present a technique for synthesizing the mouth movement from acoustic speech information. The algorithm maps the audio parameter set to the visual parameter set using the Gaussian mixture model and the hidden Markov model. With this
Autor:
Tsuhan Chen, Fu Jie Huang
Publikováno v:
MMSP
We propose a method for integrating audio and visual information to enhance speech recognition in adverse environments. We train the audio hidden Markov model and the visual hidden Markov model separately, and then use a Viterbi algorithm to decode b
Autor:
Tsuhan Chen, Fu Jie Huang
Publikováno v:
IEEE International Conference on Multimedia and Expo (III)
Describes a real-time face-tracking algorithm. We start with single face tracking based on statistical color modeling and a deformable template. We then expand the algorithm to track multiple faces, possibly with occlusion, by constraining the speed
Publikováno v:
FG
We describe a novel neural network architecture, which can recognize human faces with any view in a certain viewing angle range (from left 30 degrees to right 30 degrees out of plane rotation). View-specific eigenface analysis is used as the front-en
Publikováno v:
ICASSP
Concatenative visual speech synthesis selects frames from a large recorded video database of mouth shapes to generate photo-realistic talking head sequences. The synthesized sequence must exhibit precise lip-sound synchronization and smooth articulat
Publikováno v:
IEEE International Conference on Acoustics Speech and Signal Processing.