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Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

Published on: December 15, 2023

Scalable mobile image retrieval by exploring contextual saliency.

Xiyu Yang, Xueming Qian, Yao Xue

IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society

|March 17, 2015

Summary

This summary is machine-generated.

This study introduces a mobile image retrieval method using contextual saliency from multiple photos. It achieves better performance with significantly less data, ideal for limited bandwidth scenarios.

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Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

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A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

Published on: January 18, 2020

Area of Science:

Computer Science
Information Retrieval

Background:

Smartphones facilitate easy photo capture and sharing via social networks.
Users often take multiple photos to ensure content quality, leading to redundant data.

Purpose of the Study:

To propose an effective and scalable mobile image retrieval approach.
To leverage contextual salient information from multiple relevant photos for enhanced retrieval.
To explore high-level semantic information beyond single input images.

Main Methods:

Visually identify relevant photos for a given query image.
Mine salient features by analyzing contextual saliency across multiple images.
Determine feature contributions for efficient and scalable retrieval.

Main Results:

The proposed approach significantly reduces bandwidth requirements (<200-B data, <5% of existing methods).
Achieves superior retrieval performance compared to current mobile-based techniques.
Enables feature ranking based on contribution, optimizing retrieval under limited bandwidth.

Conclusions:

The developed mobile image retrieval method is effective and efficient.
Contextual saliency exploration offers a powerful alternative to single-image retrieval.
The approach is particularly beneficial for resource-constrained mobile environments.