Smooth Downsampling of Depth Images for Visual Prostheses
محل انتشار: نهمین کنفرانس ماشین بینایی و پردازش تصویر ایران
سال انتشار: 1394
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 480
نسخه کامل مقاله در کنفرانس ارائه نشده است و در دسترس نیست.
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
این مقاله در بخشهای موضوعی زیر دسته بندی شده است:
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
ICMVIP09_068
تاریخ نمایه سازی: 6 اسفند 1395
چکیده مقاله:
Over the past few decades, a variety of visual prostheses is developed to allow for the restoration of the vision for the blind. In visual prostheses, visual perception is limited to extremely low image resolution mainly due to restrictions in the fabrication of efficient microelectrode arrays. As a result, tasks such as navigation and way finding become difficult for thoseusing implantable visual prostheses. Depth cue is a suitable alternative to intensity images to improve the quality and success of the aforementioned tasks in patients. After the processing of depth images, intensity of an object depends on its distance from the patient. Based on this principle, a method for preprocessing and downsampling of the depth images is proposed in this paper. We propose a method to enhance the contrast of the depth images and downsample the results to 6 × 12 images. This paper analyzes common downsampling methods and proposes a methodbased on the mode function. In the proposed method, the mode function is applied on every four successive frames to use temporal information in addition to stationary information. Quantitative and qualitative evaluations upon the LIRIS dataset are presented to compare the results of proposed method with rivals
کلیدواژه ها:
نویسندگان
Benyamin Kheradvar
Faculties of Electrical and Computer Engineering, K.N. Toosi University of Technology, Tehran, Iran
Amir Mousavinia
Faculties of Electrical and Computer Engineering, K.N. Toosi University of Technology, Tehran, Iran
Amir M. Sodagar
Research Lab. for Integrated Circuits and Systems, Faculty of E.E., K.N. Toosi University of Technology, Tehran, Iran