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ICML
2000
IEEE
15 years 10 months ago
Maximum Entropy Markov Models for Information Extraction and Segmentation
Hidden Markov models (HMMs) are a powerful probabilistic tool for modeling sequential data, and have been applied with success to many text-related tasks, such as part-of-speech t...
Andrew McCallum, Dayne Freitag, Fernando C. N. Per...
ICIAP
2003
ACM
15 years 10 months ago
A topological approach for segmenting human body shape
Segmentation of 3D human body is a very challenging problem in applications exploiting human scan data. To tackle this problem, this paper proposes a topological approach based on...
Yijun Xiao, Naoufel Werghi, Paul Siebert
ICASSP
2009
IEEE
15 years 4 months ago
Genre effects on automatic sentence segmentation of speech: A comparison of broadcast news and broadcast conversations
We investigate genre effects on the task of automatic sentence segmentation, focusing on two important domains – broadcast news (BN) and broadcast conversation (BC). We employ a...
Jáchym Kolár, Yang Liu, Elizabeth Sh...
ICAT
2007
IEEE
15 years 4 months ago
Compensated Visual Hull for Defective Segmentation and Occlusion
We propose an advanced visual hull technique to compensate for outliers using reliabilities of the silhouettes. The proposed method consists of a foreground extraction technique b...
Hansung Kim, Ryuuki Sakamoto, Itaru Kitahara, Neal...
HAPTICS
2002
IEEE
15 years 2 months ago
Building a Task Language for Segmentation and Recognition of User Input to Cooperative Manipulation Systems
We present the results of using Hidden Markov Models (HMMs) for automatic segmentation and recognition of user motions. Previous work on recognition of user intent with man/machin...
C. Sean Hundtofte, Gregory D. Hager, Allison M. Ok...