Paper Info
Title
Dynamic Saliency Model Inspired by Middle Temporal Visual Area: A Spatio-Temporal Perspective
Abstract
With the advancement in technology, digital visual data is also increasing day by day. And there is a great need to develop systems that can understand it. For computers, this is a daunting task to do but our brain efficiently and apparently effortlessly doing this task very well. This paper aims to devise a dynamic saliency model inspired by the human visual system. Most models are based on low-level image features and focus on static and dynamic images. And those models do not perform well in accordance with the human gaze movement for dynamic scenes. We here demonstrate that a combined model of bio-inspired spatio-temporal features, high-level and low-level features outperform listed models in predicting human fixation on dynamic visual input. Our comparison with other models is based on eye-movement recordings of human participants observing dynamic natural scenes.
Year
DOI
Venue
2018
10.1109/DICTA.2018.8615806
2018 Digital Image Computing: Techniques and Applications (DICTA)
Keywords
Field
DocType
Visual saliency,Low-level features,High level features,Spatio-Temporal coherence,Visual cortex,Center bias
Computer vision,Pattern recognition,Gaze,Visual cortex,Computer science,Feature (computer vision),Visualization,Human visual system model,Salience (neuroscience),Feature extraction,Artificial intelligence,Optical imaging
Conference
ISBN
Citations 
PageRank 
978-1-5386-6603-6
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Hassan Mahmood100.34
Syed Mohammed Shamsul Islam2104.43
Syed Omer Gilani35912.83
Yasar Ayaz46311.39