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Related Experiment Video

Updated: Jul 7, 2026

End-To-End Deep Neural Network for Salient Object Detection in Complex Environments

End-To-End Deep Neural Network for Salient Object Detection in Complex Environments

Published on: December 15, 2023

An image model based on occluding object images and maximum entropy.

J A Stuller¹, R Shah

¹Department of Electrical and Computer Engineering, University of Missouri-Rolla, Rolla, MO 65409-0040, USA. stuller@ece.umr.edu

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

|February 16, 2008

Summary

This summary is machine-generated.

This study presents a new statistical image model incorporating occlusion and maximum entropy principles. The model accounts for random object positions, shapes, and intensities, improving image analysis.

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Creating Objects and Object Categories for Studying Perception and Perceptual Learning

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Published on: November 2, 2012

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End-To-End Deep Neural Network for Salient Object Detection in Complex Environments

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Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

Area of Science:

Computer Vision
Statistical Modeling
Image Processing

Background:

Image formation involves complex interactions like occlusion.
Existing models may not fully capture non-uniform object intensities and shapes.

Purpose of the Study:

Introduce a novel statistical image model.
Incorporate occlusion and maximum entropy for enhanced image representation.

Main Methods:

Developed a statistical model based on object-image composition.
Objects possess random positions, shapes, and intensities.
Modeled occlusion between objects and background.

Main Results:

Derived autocorrelation functions for the statistical model.
Derived second-order probability density functions.
Demonstrated model utility with several examples.

Conclusions:

The proposed model effectively integrates occlusion and maximum entropy.
Provides a robust framework for analyzing images with complex object interactions.