Title
The Computation Reduction In Object Detection Via Composite Structure Of Modified Integral Images
Abstract
Object detection is the first step in the object recognition. According to the detection results, its following works are affected. However, object detection has a heavy resource requirement in terms of, computing power and memory. If an image is enlarged, the computational load required for object detection is also increased. An-integral-image-based method guarantees fast object detection. Once an integral image is generated, the speed of the object detection procedure remains fixed, regardless of the pattern region size. However, this becomes an even greater issue if the image is enlarged. In this paper, we propose the use of directional integral image based object detection. A directional integral image gives direction to an integral image, which can then be calculated from various directions. Furthermore, many unnecessary calculations, which typically occur when a partial integral image is used for object detection, can be avoided. Therefore, the amount of computation is reduced, compared with methods using integral images. In experiments comparing methods, the proposed method required 40% fewer computations.
Year
DOI
Venue
2017
10.1587/transinf.2016EDL8158
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
Keywords
Field
DocType
directional integral image, integral image, composite-type directional integral image
Object detection,Computer vision,Computer science,Composite number,Artificial intelligence,Computation
Journal
Volume
Issue
ISSN
E100D
1
1745-1361
Citations 
PageRank 
References 
0
0.34
1
Authors
4
Name
Order
Citations
PageRank
Daeha Lee183.69
Jaehong Kim238341.59
Ho-Hee Kim300.34
Soon-Ja Kim400.34