A fast object recognition and categorization technique for robot grasping using the visual bag of words

2016 ◽  
Author(s):  
Mohamed Hannat ◽  
Nabila Zrira ◽  
Younes Raoui ◽  
El Houssine Bouyakhf
Keyword(s):  
Object Recognition ◽  
Bag Of Words ◽  
Robot Grasping

Object recognition and robot grasping technology based on RGB-D data

2020 ◽  
Author(s):  
Sheng Yu ◽  
Di-Hua Zhai ◽  
Haocun Wu ◽  
Hongda Yang ◽  
Yuanqing Xia
Keyword(s):  
Object Recognition ◽  
Robot Grasping

scholarly journals Cloud-based robot grasping with the google object recognition engine

2013 ◽  
Author(s):  
Ben Kehoe ◽  
Akihiro Matsukawa ◽  
Sal Candido ◽  
James Kuffner ◽  
Ken Goldberg
Keyword(s):  
Object Recognition ◽  
Robot Grasping

A Study of Household Object Recognition Using SIFT-Based Bag-of-Words Dictionary and SVMs

2015 ◽  
pp. 573-580 ◽  
Author(s):  
Aadarsh Sampath ◽  
Aravind Sivaramakrishnan ◽  
Keshav Narayan ◽  
R. Aarthi
Keyword(s):  
Object Recognition ◽  
Bag Of Words

20Clustered Domain Colors and Bag of Words Algorithm Based Image Retrieval

2013 ◽  
Vol 321-324 ◽  
pp. 956-960 ◽  
Author(s):  
Lei Tang ◽  
Chang Sheng Zhou ◽  
Liang Zhang
Keyword(s):  
Object Recognition ◽  
Image Retrieval ◽  
Search Algorithm ◽  
Recognition Algorithm ◽  
Features Extraction ◽  
Bag Of Words ◽  
Semantic Features ◽  
Color Information ◽  
Visual Words ◽  
Detection And Recognition

Bag of words algorithm is an efficient object recognition algorithm based on semantic features extraction and expression. It learns the virtues of the text-based search algorithm to make images a range of visual words, extract the semantic characters and carry out the detection and recognition of interesting objects. Bag of words algorithm is extracted from gray images and discard s color information of images. We propose in this paper a method of image retrieval based on clustered domain colors and bag of words algorithm. The results of experiments show that this method can improve the precision of retrieval efficiently.

scholarly journals Fusing Color and Shape for Bag-of-Words Based Object Recognition

2013 ◽  
pp. 25-34 ◽  
Author(s):  
Joost van de Weijer ◽  
Fahad Shahbaz Khan
Keyword(s):  
Object Recognition ◽  
Bag Of Words

Research on Bioinformatics with Sparse Feature Fusion for Object Recognition

2013 ◽  
Vol 830 ◽  
pp. 485-489
Author(s):  
Shu Fang Wu ◽  
Jie Zhu ◽  
Zhao Feng Zhang
Keyword(s):  
Object Recognition ◽  
Sparse Coding ◽  
Feature Fusion ◽  
Image Representation ◽  
Experimental Results ◽  
Bag Of Words ◽  
Fusion Algorithm ◽  
Fusion Methods

Combining multiple bioinformatics such as shape and color is a challenging task in object recognition. Usually, we believe that if more different bioinformatics are considered in object recognition, then we could get better result. Bag-of-words-based image representation is one of the most relevant approaches; many feature fusion methods are based on this model. Sparse coding has attracted a considerable amount of attention in many domains. A novel sparse feature fusion algorithm is proposed to fuse multiple bioinformatics to represent the images. Experimental results show good performance of the proposed algorithm.

Object recognition using bag of words with kernels for big data

2014 ◽  
Author(s):  
Cheyu Wu ◽  
Ching-Te Chiu ◽  
Yar-Sun Hsu
Keyword(s):  
Big Data ◽  
Object Recognition ◽  
Bag Of Words

The Impact of Color on Bag-of-Words Based Object Recognition

2010 ◽  
Author(s):  
David Augusto Rojas Vigo ◽  
Fahad Shahbaz Khan ◽  
Joost van de Weijer ◽  
Theo Gevers
Keyword(s):  
Object Recognition ◽  
Bag Of Words ◽  
The Impact
Sign in / Sign up

Export Citation Format

Share Document