Abstract
In this paper, a content-based motion estimation algorithm that extends the utilization of spatial correlation into the reference frame is proposed. This algorithm incorporates Adaptive Search Window (ASW) and Three Step Search (TSS), and realizes dynamic search strategy optimization according to local motion complexity of video contents with a new motion type prediction technique that examines local motion vector distribution of two consecutive frames. Simulation results show that the proposed method can constantly reduce the dynamic computational cost to as low as 3%∼4% of that of Full Search (FS), with the visual quality in terms of PSNR remaining very close to that of FS for various test video sequences.
| Original language | English |
|---|---|
| Title of host publication | Midwest Symposium on Circuits and Systems |
| Volume | 2 |
| Publication status | Published - 2004 |
| Event | The 2004 47th Midwest Symposium on Circuits and Systems - Conference Proceedings - Hiroshima, Japan Duration: 2004 Jul 25 → 2004 Jul 28 |
Other
| Other | The 2004 47th Midwest Symposium on Circuits and Systems - Conference Proceedings |
|---|---|
| Country | Japan |
| City | Hiroshima |
| Period | 04/7/25 → 04/7/28 |
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ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Electronic, Optical and Magnetic Materials
Cite this
Content-based motion estimation with extended temporal-spatial analysis. / Li, Shen; Jiang, Yong; Ikenaga, Takeshi; Goto, Satoshi.
Midwest Symposium on Circuits and Systems. Vol. 2 2004.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Content-based motion estimation with extended temporal-spatial analysis
AU - Li, Shen
AU - Jiang, Yong
AU - Ikenaga, Takeshi
AU - Goto, Satoshi
PY - 2004
Y1 - 2004
N2 - In this paper, a content-based motion estimation algorithm that extends the utilization of spatial correlation into the reference frame is proposed. This algorithm incorporates Adaptive Search Window (ASW) and Three Step Search (TSS), and realizes dynamic search strategy optimization according to local motion complexity of video contents with a new motion type prediction technique that examines local motion vector distribution of two consecutive frames. Simulation results show that the proposed method can constantly reduce the dynamic computational cost to as low as 3%∼4% of that of Full Search (FS), with the visual quality in terms of PSNR remaining very close to that of FS for various test video sequences.
AB - In this paper, a content-based motion estimation algorithm that extends the utilization of spatial correlation into the reference frame is proposed. This algorithm incorporates Adaptive Search Window (ASW) and Three Step Search (TSS), and realizes dynamic search strategy optimization according to local motion complexity of video contents with a new motion type prediction technique that examines local motion vector distribution of two consecutive frames. Simulation results show that the proposed method can constantly reduce the dynamic computational cost to as low as 3%∼4% of that of Full Search (FS), with the visual quality in terms of PSNR remaining very close to that of FS for various test video sequences.
UR - http://www.scopus.com/inward/record.url?scp=11144260203&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=11144260203&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:11144260203
VL - 2
BT - Midwest Symposium on Circuits and Systems
ER -