Adaptive wavelet eye-gaze based video compression

Mohsen Farid; Fatih Kurugollu; Fionn Murtagh

doi:10.1117/12.464354

Adaptive wavelet eye-gaze based video compression

Mohsen Farid, Fatih Kurugollu, Fionn Murtagh

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

Abstract

We present a novel approach to compression of video frames based on the foveation behavior of the human visual system (HSV). Eye fixations on a video frame, as depicted by eye-gaze trace data, define an imaginary region of interest. The perceived resolution of the frame by the human eye depends totally on this eye-gaze (fixation) point. The resolution, then, decreases dramatically with the distance from the fovea. This behavior of the HSV has gained interest in the image and video processing area recently especially in compression of images or video frames. We present an approach where eye-gaze trace data are integral to the compression process which has demonstrated its usefulness in yielding high compression performance. We partition a video frame into three regions: the inner-most includes a point of eye-gaze for which we apply lossless compression; an outer region which encompasses the first and for which we apply visually lossless (near-lossless) compression, and finally an outmost region where lossy compression is applied. Because of its low computational complexity, we use the Haar wavelet transform. Preliminary results are promising and show improvement over other methods which are mainly full frame based.

Original language	English
Title of host publication	Opto-Ireland 2002
Subtitle of host publication	Optical Metrology, Imaging, and Machine Vision
Editors	Andrew Shearer, Fionn D. Murtagh, James Mahon, Paul F. Whelan
Publisher	SPIE
Pages	255-263
Number of pages	9
Volume	4877
ISBN (Print)	0819446580, 9780819446589
DOIs	https://doi.org/10.1117/12.464354
Publication status	Published - 19 Mar 2003
Externally published	Yes
Event	Opto-Ireland 2002: Optical metrology, Imaging, and Machine Vision - Galway, Ireland Duration: 5 Sep 2002 → 6 Sep 2002 https://www.researchgate.net/publication/260899755_Opto-Ireland_2002_Optical_Metrology_Imaging_and_Machine_Vision

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Publisher	SPIE
Volume	4877
ISSN (Print)	0277-786X

Conference

Conference	Opto-Ireland 2002: Optical metrology, Imaging, and Machine Vision
Country/Territory	Ireland
City	Galway
Period	5/09/02 → 6/09/02
Internet address	https://www.researchgate.net/publication/260899755_Opto-Ireland_2002_Optical_Metrology_Imaging_and_Machine_Vision

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Farid, M., Kurugollu, F., & Murtagh, F. (2003). Adaptive wavelet eye-gaze based video compression. In A. Shearer, F. D. Murtagh, J. Mahon, & P. F. Whelan (Eds.), Opto-Ireland 2002: Optical Metrology, Imaging, and Machine Vision (Vol. 4877, pp. 255-263). (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 4877). SPIE. https://doi.org/10.1117/12.464354

@inproceedings{d3057f24ae674678983deaafd0aa7cd3,

title = "Adaptive wavelet eye-gaze based video compression",

abstract = "We present a novel approach to compression of video frames based on the foveation behavior of the human visual system (HSV). Eye fixations on a video frame, as depicted by eye-gaze trace data, define an imaginary region of interest. The perceived resolution of the frame by the human eye depends totally on this eye-gaze (fixation) point. The resolution, then, decreases dramatically with the distance from the fovea. This behavior of the HSV has gained interest in the image and video processing area recently especially in compression of images or video frames. We present an approach where eye-gaze trace data are integral to the compression process which has demonstrated its usefulness in yielding high compression performance. We partition a video frame into three regions: the inner-most includes a point of eye-gaze for which we apply lossless compression; an outer region which encompasses the first and for which we apply visually lossless (near-lossless) compression, and finally an outmost region where lossy compression is applied. Because of its low computational complexity, we use the Haar wavelet transform. Preliminary results are promising and show improvement over other methods which are mainly full frame based.",

keywords = "ASL-504, Eye-tracking, Foveation, Video compression, Wavelet transform, Video, Image compression, Wavelets, Eye, Visualization, RGB color model, Video processing, Video coding",

author = "Mohsen Farid and Fatih Kurugollu and Fionn Murtagh",

year = "2003",

month = mar,

day = "19",

doi = "10.1117/12.464354",

language = "English",

isbn = "0819446580",

volume = "4877",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

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booktitle = "Opto-Ireland 2002",

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note = "Opto-Ireland 2002: Optical metrology, Imaging, and Machine Vision ; Conference date: 05-09-2002 Through 06-09-2002",

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Farid, M, Kurugollu, F & Murtagh, F 2003, Adaptive wavelet eye-gaze based video compression. in A Shearer, FD Murtagh, J Mahon & PF Whelan (eds), Opto-Ireland 2002: Optical Metrology, Imaging, and Machine Vision. vol. 4877, Proceedings of SPIE - The International Society for Optical Engineering, vol. 4877, SPIE, pp. 255-263, Opto-Ireland 2002: Optical metrology, Imaging, and Machine Vision, Galway, Ireland, 5/09/02. https://doi.org/10.1117/12.464354

Adaptive wavelet eye-gaze based video compression. / Farid, Mohsen; Kurugollu, Fatih; Murtagh, Fionn.

Opto-Ireland 2002: Optical Metrology, Imaging, and Machine Vision. ed. / Andrew Shearer; Fionn D. Murtagh; James Mahon; Paul F. Whelan. Vol. 4877 SPIE, 2003. p. 255-263 (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 4877).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - We present a novel approach to compression of video frames based on the foveation behavior of the human visual system (HSV). Eye fixations on a video frame, as depicted by eye-gaze trace data, define an imaginary region of interest. The perceived resolution of the frame by the human eye depends totally on this eye-gaze (fixation) point. The resolution, then, decreases dramatically with the distance from the fovea. This behavior of the HSV has gained interest in the image and video processing area recently especially in compression of images or video frames. We present an approach where eye-gaze trace data are integral to the compression process which has demonstrated its usefulness in yielding high compression performance. We partition a video frame into three regions: the inner-most includes a point of eye-gaze for which we apply lossless compression; an outer region which encompasses the first and for which we apply visually lossless (near-lossless) compression, and finally an outmost region where lossy compression is applied. Because of its low computational complexity, we use the Haar wavelet transform. Preliminary results are promising and show improvement over other methods which are mainly full frame based.

AB - We present a novel approach to compression of video frames based on the foveation behavior of the human visual system (HSV). Eye fixations on a video frame, as depicted by eye-gaze trace data, define an imaginary region of interest. The perceived resolution of the frame by the human eye depends totally on this eye-gaze (fixation) point. The resolution, then, decreases dramatically with the distance from the fovea. This behavior of the HSV has gained interest in the image and video processing area recently especially in compression of images or video frames. We present an approach where eye-gaze trace data are integral to the compression process which has demonstrated its usefulness in yielding high compression performance. We partition a video frame into three regions: the inner-most includes a point of eye-gaze for which we apply lossless compression; an outer region which encompasses the first and for which we apply visually lossless (near-lossless) compression, and finally an outmost region where lossy compression is applied. Because of its low computational complexity, we use the Haar wavelet transform. Preliminary results are promising and show improvement over other methods which are mainly full frame based.

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KW - RGB color model

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SN - 0819446580

SN - 9780819446589

VL - 4877

T3 - Proceedings of SPIE - The International Society for Optical Engineering

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Y2 - 5 September 2002 through 6 September 2002

ER -

Adaptive wavelet eye-gaze based video compression

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