Publications by Gökhan Yildirim

Evaluating salient object detection in natural images with multiple objects having multi-level saliency

Salient object detection is evaluated using binary ground truth (GT) with the labels being salient object class and background. In this study, the authors corroborate based on three subjective experiments on a novel image dataset that objects in natural im ...

2020

Modeling the Importance of Faces in Natural Images

Sabine Süsstrunk, Appu Shaji, Cheryl Shaulya Lau, Gökhan Yildirim, Bin Jin

In this work we study the varying importance of faces in images. Face importance is found to be affected by the size and number of faces present. We collected a dataset of 152 face images with faces in different size and number of faces. We conducted a cro ...

Spie-Int Soc Optical Engineering2015

Are All Pixels Equally Important? Towards Multi-Level Salient Object Detection

Gökhan Yildirim

When we look at our environment, we primarily pay attention to visually distinctive objects. We refer to these objects as visually important or salient. Our visual system dedicates most of its processing resources to analyzing these salient objects. An ana ...

EPFL2015

FASA: Fast, Accurate, and Size-Aware Salient Object Detection

Sabine Süsstrunk, Gökhan Yildirim

Fast and accurate salient-object detectors are important for various image processing and computer vision applications, such as adaptive compression and object segmentation. It is also desirable to have a detector that is aware of the position and the size ...

Springer-Verlag Berlin2015

Saliency Detection Using Regression Trees on Hierarchical Image Segments

Sabine Süsstrunk, Appu Shaji, Gökhan Yildirim

The currently best performing state-of-the-art saliency detection algorithms incorporate heuristic functions to evaluate saliency. They require parameter tuning, and the relationship between the parameter value and visual saliency is often not well underst ...

2014

Estimating Beauty Ratings of Videos using Supervoxels

Sabine Süsstrunk, Appu Shaji, Gökhan Yildirim

The major low-level perceptual components that influence the beauty ratings of video are color, contrast, and motion. To estimate the beauty ratings of the NHK dataset, we propose to extract these features based on supervoxels, which are a group of pixels ...

2013

Rare is Interesting: Connecting Spatio-Temporal Behavior Patterns with Subjective Image Appeal

Sabine Süsstrunk, Gökhan Yildirim

We analyze behavior patterns and photographic habits of the Nokia Mobile Data Challenge (NMDC) participants using GPS and timestamp data. We show that these patterns and habits can be used to estimate image appeal ratings of geotagged Flickr images. In ord ...

2013

Low-Level Salient Region Detection Using Multi-Scale Filtering

Sabine Süsstrunk, Gökhan Yildirim

Various computer visions tasks require a summary of visually important regions in an image. Thus, developing simple yet accurate salient region detection algorithms has become an important research topic. The currently best performing state-of-the-art sali ...

2013

Text Recognition in Natural Images Using Multiclass Hough Forests

Sabine Süsstrunk, Radhakrishna Achanta, Gökhan Yildirim

Text detection and recognition in natural images are popular yet unsolved problems in computer vision. In this paper, we propose a technique that attempts to detect and recognize text in a unified manner by searching for words directly without reducing the ...

2013