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» Learning Semantic Scene Models by Trajectory Analysis
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ICCV
2009
IEEE
14 years 7 months ago
Learning to predict where humans look
For many applications in graphics, design, and human computer interaction, it is essential to understand where humans look in a scene. Where eye tracking devices are not a viable ...
Tilke Judd, Krista A. Ehinger, Frédo Durand...
94
Voted
CVPR
2008
IEEE
15 years 11 months ago
Discriminative learned dictionaries for local image analysis
Sparse signal models have been the focus of much recent research, leading to (or improving upon) state-of-the-art results in signal, image, and video restoration. This article ext...
Julien Mairal, Francis Bach, Jean Ponce, Guillermo...
TSMC
2008
147views more  TSMC 2008»
14 years 9 months ago
Tracking of Multiple Targets Using Online Learning for Reference Model Adaptation
Recently, much work has been done in multiple ob-4 ject tracking on the one hand and on reference model adaptation5 for a single-object tracker on the other side. In this paper, we...
Franz Pernkopf
COGCOM
2011
228views more  COGCOM 2011»
14 years 4 months ago
Clustering of Gaze During Dynamic Scene Viewing is Predicted by Motion
Where does one attend when viewing dynamic scenes? Research into the factors influencing gaze location during static scene viewing have reported that low-level visual features con...
Parag K. Mital, Tim J. Smith, Robin L. Hill, John ...
DAGM
2008
Springer
14 years 11 months ago
Comparing Local Feature Descriptors in pLSA-Based Image Models
Abstract. Probabilistic models with hidden variables such as probabilistic Latent Semantic Analysis (pLSA) and Latent Dirichlet Allocation (LDA) have recently become popular for so...
Eva Hörster, Thomas Greif, Rainer Lienhart, M...