Furniture  Extrac-on  From  Designed  Home  Decora-on  and  its  Matching    Guang Yang1, Chunliang Zheng2!

Department of Energy Resources Engineering1, Department of Electrical Engineering2, Stanford University

Motivation Work Flow & Methodology

Related Work

•  Parse furniture items from designed indoor scheme and find similar ones for users’ own decoration in laptop.

•  Use a handy android mobile application to quickly get information of the furniture items of interest in real life .

Android Client                                

Feature  Matching  /  Image  Retrieval      

Image  Segmenta5on  

Object    Recogni5on    

Server

1.  Harris  Keypoint  detec5on  2.  Watershed.    3.  Coutours  based.      

 SVM  classifiers.          

Matlab

Contour  based  shape  matching         MexOpenCV

Vlfeat

Experimental Results

1. MexOpenCV library, Kota Yamaguchi, Stony Brook University

2. Caltech 101 Object Recognition, L. Fei-Fei, R. Fergus and P. Perona, CalTech University

3. Contour Correspondence via Colony Optimization, Oliver van Kaick, Simon Fraser University

4. Berkeley Segmentation Benchmark, UC Berkeley

Intermediate Results

Right: Watershed

Left: Harris Keypoint Detection

                 Combining  three  segmenta5on  techniques,  we  get    preKy  nice  results.(shown  in  demo)                          Contour  shape  matching  is  computa5onal  efficient  and  works  properly  for  furniture  matching.