NDLI: A saliency based motion detection model of visual system considering visual adaptation properties

Content Provider	IEEE Xplore Digital Library
Author	Kodama, M. Kohama, T. Yoshida, H.
Copyright Year	2015
Description	Author affiliation: Grad. Sch. of Biol.-Oriented Sci. & Technol., Kinki Univ., Wakayama, Japan (Kodama, M.) \|\| Fac. of Biol.- Oriented Sci. & Technol., Kinki Univ., Wakayama, Japan (Kohama, T.; Yoshida, H.)
Abstract	The purpose of this study is to construct a mathematical model which predicts saliency regions in high-speed egocentric-motion movies, filmed by an embedded camera in a driving vehicle, by reproducing the characteristics of the area MT and MST neurons' receptive fields with consideration of visual adaptation properties. The area MT neurons integrate from the area V1 activation and respond well to regions where higher motion contrasts exist. While the area MST neurons detect global motions such as expansion, contraction, rotation, and so on. We modeled the area MT neurons' receptive fields as a center-surround spatial summation of counter sided motion vectors of visual scenery. The area MST neurons in our model integrate the responses of the MT neurons by convolving with spacial weight functions of which central portions are biased to preferred direction. Visual adaptations were taken as the primary delay filters for each visual feature channel to deplete the saliency of stationary objects and regions during particular frames. The simulation results for the movies which were taken in a running vehicle indicate that the proposed model detects more salient objects around the vanishing point than the conventional saliency based model. To evaluate the performance of proposed model, we defined the moving-NSS (normalized scan-path salience) scores as the averaged NSS scores in each moving time window. The moving-NSS scores for motion images of our model were higher than those of the conventional model.
Starting Page	6658
Ending Page	6661
File Size	4497514
Page Count	4
File Format	PDF
ISSN	1557170X
e-ISBN	9781424492718
DOI	10.1109/EMBC.2015.7319920
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-25
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Adaptation models Visualization Predictive models Motion pictures Simulation Neurons Vehicles
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Motion sensitivity analysis of retinal ganglion cells in mouse retina using natural visual stimuli

Internal models engaged by brain-computer interface control

Anticipatory visual perception as a bio-inspired mechanism underlying robot locomotion

An face-based visual fixation system for prosthetic vision

Prediction of single neuron spiking activity using an optimized nonlinear dynamic model

Fuzzy-based simulation of real color blindness

Label Consistent Quadratic Surrogate model for visual saliency prediction

Prosthesis-user-in-the-loop: User-centered design parameters and visual simulation

Motion visual stimulus for SSVEP-based BCI system

A saliency based motion detection model of visual system considering visual adaptation properties

Similar Documents

Motion sensitivity analysis of retinal ganglion cells in mouse retina using natural visual stimuli

Internal models engaged by brain-computer interface control

Anticipatory visual perception as a bio-inspired mechanism underlying robot locomotion

An face-based visual fixation system for prosthetic vision

Prediction of single neuron spiking activity using an optimized nonlinear dynamic model

Fuzzy-based simulation of real color blindness

Label Consistent Quadratic Surrogate model for visual saliency prediction

Prosthesis-user-in-the-loop: User-centered design parameters and visual simulation

Motion visual stimulus for SSVEP-based BCI system

A saliency based motion detection model of visual system considering visual adaptation properties