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Saliency-based Representations and Multi-component Classifiers for Visual Scene Recognition

Related publications (211)

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Frequency-tuned Salient Region Detection

Sabine Süsstrunk, Radhakrishna Achanta, Francisco Estrada

Detection of visually salient image regions is useful for applications like object segmentation, adaptive compression, and object recognition. In this paper, we introduce a method for salient region detection that outputs full resolution saliency maps with ...

2009

Image Summaries using Database Saliency

Pascal Fua, Sabine Süsstrunk, Radhakrishna Achanta, Appu Shaji

It is useful to have a small set of representative images from a database of thousands of images to summarize its content. There are two key aspects of such image summaries: how to generate them and how to present them. We address both issues. We extend th ...

2009

Who's Doing What: Joint Modeling of Names and Verbs for Simultaneous Face and Pose Annotation

Barbara Caputo, Jie Luo, Vittorio Ferrari

Given a corpus of news items consisting of images accompanied by text captions, we want to find out “who’s doing what”, i.e. associate names and action verbs in the captions to the face and body pose of the persons in the images. We present a joint model f ...

MIT Press2009

Saliency Detection for Content-aware Image Resizing

Sabine Süsstrunk, Radhakrishna Achanta

Content aware image re-targeting methods aim to arbitrarily change image aspect ratios while preserving visually prominent features. To determine visual importance of pixels, existing re-targeting schemes mostly rely on grayscale intensity gradient maps. T ...

2009

A collaborative approach to image segmentation and behavior recognition from image sequences

Laura Ioana Gui

Visual behavior recognition is currently a highly active research area. This is due both to the scientific challenge posed by the complexity of the task, and to the growing interest in its applications, such as automated visual surveillance, human-computer ...

EPFL2008

Semantic coding by supervised dimensionality reduction

Pascal Frossard, Effrosyni Kokiopoulou

This paper addresses the problem of representing multimedia information under a compressed form that permits efficient classification. The semantic coding problem starts from a subspace method where dimensionality reduction is formulated as a matrix factor ...

2008

Cue Integration for Medical Image Annotation

Barbara Caputo, Tatiana Tommasi

This paper presents the algorithms and results of our par- ticipation to the image annotation task of ImageCLEFmed 2007. We proposed a multi-cue approach where images are represented both by global and local descriptors. These cues are combined following t ...

Springer-Verlag2008

Towards Robust Place Recognition for Robot Localization

Barbara Caputo, Jie Luo

Localization and context interpretation are two key competences for mobile robot systems. Visual place recognition, as opposed to purely geometrical models, holds promise of higher flexibility and association of semantics to the model. Ideally, a place rec ...

2008

Distributed target localization via spatial sparsity

Volkan Cevher

We propose an approximation framework for distributed target localization in sensor networks. We represent the unknown target positions on a location grid as a sparse vector, whose support encodes the multiple target locations. The location vector is linea ...

2008

Keypoint Signatures for Fast Learning and Recognition

Pascal Fua, Vincent Lepetit, Michael Calonder

Statistical learning techniques have been used to dramatically speed-up keypoint matching by training a classifier to recognize a specific set of keypoints. However, the training itself is usually relatively slow and performed offline. Although methods hav ...

2008