What question did this study set out to answer?

This research aims to define what makes an object in an image distinct by integrating various algorithms.

June 1, 2013

What Makes a Patch Distinct?

RMRan MargolinTechnion – Israel Institute of Technology ATAyellet TalTechnion – Israel Institute of Technology LZLihi Zelnik‐ManorTechnion – Israel Institute of Technology

Key Points

This research aims to define what makes an object in an image distinct by integrating various algorithms.
Proposed a new algorithm that combines patterns, colors, and high-level cues.
Evaluated the algorithm against existing state-of-the-art methods.
Used five commonly-used datasets for extensive performance evaluation.
Demonstrated superior performance compared to existing algorithms on all five datasets.
Provided evidence that integrating diverse measures improves pattern distinctness.

Abstract

What makes an object salient? Most previous work assert that distinctness is the dominating factor. The difference between the various algorithms is in the way they compute distinctness. Some focus on the patterns, others on the colors, and several add high-level cues and priors. We propose a simple, yet powerful, algorithm that integrates these three factors. Our key contribution is a novel and fast approach to compute pattern distinctness. We rely on the inner statistics of the patches in the image for identifying unique patterns. We provide an extensive evaluation and show that our approach outperforms all state-of-the-art methods on the five most commonly-used datasets.

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