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NIPS
2001
13 years 8 months ago
Unsupervised Learning of Human Motion Models
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...
Yang Song, Luis Goncalves, Pietro Perona
IROS
2007
IEEE
129views Robotics» more  IROS 2007»
14 years 1 months ago
Representability of human motions by factorial hidden Markov models
— This paper describes an improved methodology for human motion recognition and imitation based on Factorial Hidden Markov Models (FHMM). Unlike conventional Hidden Markov Models...
Dana Kulic, Wataru Takano, Yoshihiko Nakamura
AAIP
2009
13 years 8 months ago
Incremental Learning in Inductive Programming
Inductive programming systems characteristically exhibit an exponential explosion in search time as one increases the size of the programs to be generated. As a way of overcoming ...
Robert Henderson
AVSS
2005
IEEE
14 years 1 months ago
Surveillance video for mobile devices
In this paper, we present a video encoding scheme that uses object-based adaptation to deliver surveillance video to mobile devices. The method relies on a set of complementary vi...
Olivier Steiger, Touradj Ebrahimi, Andrea Cavallar...
CCS
2010
ACM
13 years 10 months ago
Scene tagging: image-based CAPTCHA using image composition and object relationships
In this paper, we propose a new form of image-based CAPTCHA we term "scene tagging". It tests the ability to recognize a relationship between multiple objects in an imag...
Peter Matthews, Cliff Changchun Zou