Image Based Localization in Indoor Environments

Abstract

Abstract-Image based localization is an important problem with many applications. In our previous work, we presented a two step pipeline for performing image based localization of mobile devices in outdoor environments. In the first step, a query image is matched against a georeferenced 3D image database to retrieve the "closest" image. In the second step, the pose of the query image is recovered with respect to the "closest" image using cell phone sensors. As such, a key ingredient of our outdoor image based localization is a 3D georeferenced image database. In this paper, we extend this approach to indoors by utilizing a 3D locally referenced image database generated by an ambulatory depth acquisition backpack that is originally developed for 3D modeling of indoor environments. We demonstrate retrieval rate of 94% over a set of 83 query images taken in an indoor shopping center and characterize pose recovery accuracy of the same set.

An Original Application of Image Recognition Based Location in Complex Indoor Environments

“…Examples could be found in the research by Liang et al [10], where the image based localisation has been performed using a backpack acquiring frame and depth information at the same time for the generation of a database of reference images. This work differs from our research due to the lower resolution of the images and the methodology of the database creation.…”

“…In recent years, some LBSs have been proposed using integration of different technologies and methods of measurements [1]. Cameras [9][10][11], infrared (Kinect), ultrasound [12], WLAN/WiFi [13], RFID [14], mobile communication [15] and so forth are examples of the technologies that the scientific community has put at the service of indoor locations. All these positioning systems have pros and cons that make them more useful in specific scenarios, compared to other options.…”

Visual Map Construction Using RGB-D Sensors for Image-Based Localization in Indoor Environments

“…An evident disadvantage of these localization systems is that Wi-Fi hotspots or Bluetooth beacons as anchor points cannot be moved after the initial calibration. Moreover, if high localization accuracy is required by indoor navigation systems, for example, submeter accuracy, Wi-Fi hotspots or Bluetooth beacons must be densely distributed in public areas [9]. However, in some public buildings, such as railway stations and airports, high-density infrastructures are costly and inconvenient to achieve.…”

“…Therefore, more and more studies have focused on the field of localization and navigation based on visual methods using smartphones [9][10][11][12][13][14][15][16][17]. Vision-based localization takes advantage of image retrieval to search for the similar geo-tagged database images for a query image, and then the location of the query image can be estimated.…”

Visual Location Recognition Based on Coarse-to-Fine Image Retrieval and Epipolar Geometry Constraint for Urban Environment

“…The Multiple Hypothesis Vocabulary Tree is introduced to reduce the complexity of the feature quantization. The authors in [7] present a completed image retrieval based pipeline for the visual location recognition.…”