VLSI architectures for stereoscopic video disparity matching and object extraction

Jian Hung Lin; Keshab K. Parhi

doi:10.1109/ISCAS.2005.1465102

VLSI architectures for stereoscopic video disparity matching and object extraction

Jian Hung Lin, Keshab K. Parhi

Electrical and Computer Engineering

Research output: Contribution to journal › Conference article › peer-review

4 Scopus citations

Abstract

Disparity matching and object extraction of stereoscopic video are critical procedures for many computer vision applications. Current research in this area is mostly focused on algorithm design for software implementation and the coding efficiency is not acceptable for many real-time applications. To overcome the problems and further improve efficiency, several hardware oriented methods and architectures are proposed. First, an improved disparity matching method referred as two-level hybrid disparity estimation is proposed which is designed for stereoscopic video and has low computational complexity and good performance. Then a new segmentation algorithm for the depth map previously obtained referred as average but keep boundary (ABKB) is proposed. Both of these algorithms are combined with an existing mean shift color segmentation algorithm to design a high speed video object extraction unit.

Original language	English (US)
Article number	1465102
Pages (from-to)	2373-2376
Number of pages	4
Journal	Proceedings - IEEE International Symposium on Circuits and Systems
DOIs	https://doi.org/10.1109/ISCAS.2005.1465102
State	Published - Dec 1 2005
Event	IEEE International Symposium on Circuits and Systems 2005, ISCAS 2005 - Kobe, Japan Duration: May 23 2005 → May 26 2005

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10.1109/ISCAS.2005.1465102

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title = "VLSI architectures for stereoscopic video disparity matching and object extraction",

abstract = "Disparity matching and object extraction of stereoscopic video are critical procedures for many computer vision applications. Current research in this area is mostly focused on algorithm design for software implementation and the coding efficiency is not acceptable for many real-time applications. To overcome the problems and further improve efficiency, several hardware oriented methods and architectures are proposed. First, an improved disparity matching method referred as two-level hybrid disparity estimation is proposed which is designed for stereoscopic video and has low computational complexity and good performance. Then a new segmentation algorithm for the depth map previously obtained referred as average but keep boundary (ABKB) is proposed. Both of these algorithms are combined with an existing mean shift color segmentation algorithm to design a high speed video object extraction unit.",

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doi = "10.1109/ISCAS.2005.1465102",

language = "English (US)",

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journal = "Proceedings - IEEE International Symposium on Circuits and Systems",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "IEEE International Symposium on Circuits and Systems 2005, ISCAS 2005 ; Conference date: 23-05-2005 Through 26-05-2005",

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T1 - VLSI architectures for stereoscopic video disparity matching and object extraction

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AU - Parhi, Keshab K.

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N2 - Disparity matching and object extraction of stereoscopic video are critical procedures for many computer vision applications. Current research in this area is mostly focused on algorithm design for software implementation and the coding efficiency is not acceptable for many real-time applications. To overcome the problems and further improve efficiency, several hardware oriented methods and architectures are proposed. First, an improved disparity matching method referred as two-level hybrid disparity estimation is proposed which is designed for stereoscopic video and has low computational complexity and good performance. Then a new segmentation algorithm for the depth map previously obtained referred as average but keep boundary (ABKB) is proposed. Both of these algorithms are combined with an existing mean shift color segmentation algorithm to design a high speed video object extraction unit.

AB - Disparity matching and object extraction of stereoscopic video are critical procedures for many computer vision applications. Current research in this area is mostly focused on algorithm design for software implementation and the coding efficiency is not acceptable for many real-time applications. To overcome the problems and further improve efficiency, several hardware oriented methods and architectures are proposed. First, an improved disparity matching method referred as two-level hybrid disparity estimation is proposed which is designed for stereoscopic video and has low computational complexity and good performance. Then a new segmentation algorithm for the depth map previously obtained referred as average but keep boundary (ABKB) is proposed. Both of these algorithms are combined with an existing mean shift color segmentation algorithm to design a high speed video object extraction unit.

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JO - Proceedings - IEEE International Symposium on Circuits and Systems

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T2 - IEEE International Symposium on Circuits and Systems 2005, ISCAS 2005

Y2 - 23 May 2005 through 26 May 2005

ER -

VLSI architectures for stereoscopic video disparity matching and object extraction

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