Journals Information
Computer Science and Information Technology Vol. 3(5), pp. 187 - 197
DOI: 10.13189/csit.2015.030504
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Visual Saliency Based Multiple Objects Segmentation and its Parallel Implementation for Real-Time Vision Processing
Hirokazu Madokoro *, Yutaka Ishioka , Satoshi Takahashi , Kazuhito Sato , Nobuhiro Shimoi
Faculty of Systems Science and Technology, Akita Prefectural University, Japan
ABSTRACT
This paper presents a segmentation method of multiple object regions based on visual saliency. Our method comprises three steps. First, attentional points are detected using saliency maps (SMs). Subsequently, regions of interest (RoIs) are extracted using scale-invariant feature transform (SIFT). Finally, foreground regions are extracted as object regions using GrabCut. Using RoIs as teaching signals, our method achieved automatic segmentation of multiple objects without learning in advance. As experimentally obtained results obtained using PASCAL2011 dataset, attentional points were extracted correctly from 18 images for two objects and from 25 images for single objects. We obtained segmentation accuracies: 64.1%, precision; 62.1%, recall, and 57.4%, F-measure. For real-time video image processing, we implemented our model on an IMAPCAR2 evaluation board. The processing cost was 47.5 ms for the video images of 640 脳 240 pixel resolution. Moreover, we applied our method to time-series images obtained using a mobile robot. Attentional points were extracted correctly for seven images for two objects and three images for single objects from ten images. We obtained segmentation accuracies of 58.0%, precision; 63.1%, recall, and 58.1%, F-measure.
KEYWORDS
Multiple Object Detection, Regional Division, Extraction of Object Regions, Saliency Maps, GrabCut
Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Hirokazu Madokoro , Yutaka Ishioka , Satoshi Takahashi , Kazuhito Sato , Nobuhiro Shimoi , "Visual Saliency Based Multiple Objects Segmentation and its Parallel Implementation for Real-Time Vision Processing," Computer Science and Information Technology, Vol. 3, No. 5, pp. 187 - 197, 2015. DOI: 10.13189/csit.2015.030504.
(b). APA Format:
Hirokazu Madokoro , Yutaka Ishioka , Satoshi Takahashi , Kazuhito Sato , Nobuhiro Shimoi (2015). Visual Saliency Based Multiple Objects Segmentation and its Parallel Implementation for Real-Time Vision Processing. Computer Science and Information Technology, 3(5), 187 - 197. DOI: 10.13189/csit.2015.030504.