You are in:Home/Publications/View Centered Video-based Object Recognition for Lightweight | |
Dr. metwally rashad metwally :: Publications: |
Title: | View Centered Video-based Object Recognition for Lightweight
|
Authors: | Czúni László and Metwally Rashad |
Year: | 2016 |
Keywords: | object recognition, view centered recognition, orientation sensor, image retrieval, KD-Tree. |
Journal: | 23rd International Conference on Systems, Signals and Image Processing (IWSSIP) |
Volume: | Not Available |
Issue: | Not Available |
Pages: | 1-4 |
Publisher: | ieeexplore.ieee |
Local/International: | International |
Paper Link: | |
Full paper | metwally rashad metwally_IWSSIP_2016 .pdf |
Supplementary materials | Not Available |
Abstract: |
Video-based object recognition faces the problem of multi-view object variance, noisy conditions, and limited computational resources. In our previous work, we introduced a multi-view recognition approach with a compact global image descriptor coupled with orientation sensor data. Since our purpose is to run all computations in a handheld device, contrary to more intensive deep learning approaches, now we investigate the efficiency of our approach using a full representation image model with KD-Tree indexing. Experimental results show the effectiveness of our approach through three databases using noisy images. |