title: Fast SIFT design for real-time visual feature extraction.
abstract: Visual feature extraction with scale invariant feature transform (SIFT) is widely used for object recognition. However, its real-time implementation suffers from long latency, heavy computation, and high memory storage because of its frame level computation with iterated Gaussian blur operations. Thus, this paper proposes a layer parallel SIFT (LPSIFT) with integral image, and its parallel hardware design with an on-the-fly feature extraction flow for real-time application needs. Compared with the original SIFT algorithm, the proposed approach reduces the computational amount by 90% and memory usage by 95%. The final implementation uses 580-K gate count with 90-nm CMOS technology, and offers 6000 feature points/frame for VGA images at 30 frames/s and ∼ 2000 feature points/frame for 1920 × 1080 images at 30 frames/s at the clock rate of 100 MHz.
authors.affiliation: PixelArt Technology, Hsinchu 78229, Taiwan. oboe.chu@gmail.com
authors.forename: Liang-Chi
authors.initials: LC
authors.lastname: Chiu
authors.forename: Tian-Sheuan
authors.initials: TS
authors.lastname: Chang
authors.forename: Jiun-Yen
authors.initials: JY
authors.lastname: Chen
authors.forename: Nelson Yen-Chung
authors.initials: NY
authors.lastname: Chang
mesh_terms: D000465:Algorithms; D003199:Computer Systems; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D010781:Photography / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014741:Video Recording / Q000379:methods*