IJBTT

A Survey on Data Association Methods in VSLAM

	International Journal of Engineering Trends and Technology (IJETT)
	© 2015 by IJETT Journal
	Volume-30 Number-2
	Year of Publication : 2015
	Authors : S.SriVidhya, Dr.C.B. Akki, Dr.Prakash S
	DOI :  10.14445/22315381/IJETT-V30P216

Citation 

S.SriVidhya, Dr.C.B. Akki, Dr.Prakash S"A Survey on Data Association Methods in VSLAM", International Journal of Engineering Trends and Technology (IJETT), V30(2),83-88 December 2015. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Abstract
In robotics the Simultaneous Localization and Mapping (SLAM) is the problem in which an autonomous robots acquires a map of the surrounding environment while at the same time localizes itself inside this map. One of the most challenging fields of research in SLAM is the so called Visual- SLAM problem, in which various types of cameras are used as sensor for the navigation. Cameras are inexpensive sensors and can provide rich information about the surrounding environment, on the other hand the complexity of the computer vision tasks and the strong dependence on the characteristics of the environment in current approaches makes the Visual-SLAM far to be considered a closed problem. Visual SLAM (simultaneous localization and mapping) refers to the problem of using images, as the only source of external information, in order to establish the position of a robot, a vehicle, or a moving camera in an environment, and at the same time, construct a representation of the explored zone. Nowadays, the problem of SLAM is considered solved when range sensors such as lasers or sonar are used to build 2D maps of small static environments. However SLAM for dynamic, complex and large scale environments, using vision as the sole external sensor, is an active area of research. The computer vision techniques employed in visual SLAM, such as detection, description and matching of salient features, image recognition and retrieval, among others, are still susceptible of improvement. The objective of this article is to provide new researchers in the field of visual SLAM a brief and comprehensible review of data association categories in VSLAM.

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Keywords
Visual SLAM - Detectors-Descriptors- Data association.