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PAMI
2011
12 years 10 months ago
Robust Object Tracking with Online Multiple Instance Learning
In this paper we address the problem of tracking an object in a video given its location in the first frame and no other information. Recently, a class of tracking techniques cal...
Boris Babenko, Ming-Hsuan Yang, Serge Belongie
CORR
2012
Springer
183views Education» more  CORR 2012»
12 years 3 months ago
Learning Determinantal Point Processes
Determinantal point processes (DPPs), which arise in random matrix theory and quantum physics, are natural models for subset selection problems where diversity is preferred. Among...
Alex Kulesza, Ben Taskar
CVPR
2012
IEEE
11 years 10 months ago
Understanding collective crowd behaviors: Learning a Mixture model of Dynamic pedestrian-Agents
In this paper, a new Mixture model of Dynamic pedestrian-Agents (MDA) is proposed to learn the collective behavior patterns of pedestrians in crowded scenes. Collective behaviors ...
Bolei Zhou, Xiaogang Wang, Xiaoou Tang
CVPR
2008
IEEE
14 years 9 months ago
Boosting adaptive linear weak classifiers for online learning and tracking
Online boosting methods have recently been used successfully for tracking, background subtraction etc. Conventional online boosting algorithms emphasize on interchanging new weak ...
Toufiq Parag, Fatih Porikli, Ahmed M. Elgammal
ICIDS
2009
Springer
14 years 2 months ago
Digital Storytelling as a Whole-Class Learning Activity: Lessons from a Three-Years Project
This paper introduces PoliCultura, a project created by Politecnico di Milano for the Italian schools, which has just completed three years of deployment. Participating classes (wi...
Nicoletta Di Blas, Franca Garzotto, Paolo Paolini,...