# General Moving Object Localization from a Single Flying Camera
###### Abstract  
Object localization is an important task in the visual surveillance of scenes, and it has important applications in locating personnel and/or equipment in large open spaces such as a farm or a mine. Traditionally, object localization can be performed using the technique of stereo vision: using two fixed cameras for a moving object, or using a single moving camera for a stationary object. This research addresses the problem of determining the location of a moving object using only a single moving camera, and it does not make use of any prior information on the type of object nor the size of the object. Our technique makes use of a single camera mounted on a quadrotor drone, which flies in a specific pattern relative to the object in order to remove the depth ambiguity associated with their relative motion. In our previous work, we showed that with three images, we can recover the location of an object moving parallel to the direction of motion of the camera. In this research, we find that with four images, we can recover the location of an object moving linearly in an arbitrary direction. We evaluated our algorithm on over 70 image sequences of objects moving in various directions, and the results showed a much smaller depth error rate (less than 8.0% typically) than other state-of-the-art algorithms.  
object localization; flying camera; ego-motion; depth ambiguity; stereo vision; depth recovery 20202  
position to take a second image, and we can make the baseline arbitrarily large [14]. Unfortunately, the object that we are tracking may have moved during that time, rendering traditional stereo vision algorithms useless [15].  
In this research, we will address the problem of determining the location of a moving object using a single moving camera. The objectives are two-fold: (1) we want to be able to make the baseline arbitrarily large; (2) we want to remove the depth ambiguity caused by a moving object relative to a moving camera. We approached this problem by mounting a single camera on a quadrotor drone and instructing it to fly in a specific pattern so as to remove the depth ambiguity associated with its relative motion. To maintain generality, we did not assume that we knew the class of the object (e.g., person, vehicle, farming equipment, etc.) or the size, speed, and direction of motion of the object. This allows us to apply this technique to various applications such as locating farm personnel and equipment, mining vehicles, delivery vehicles belonging to logistics supply chains, wild animals in a prairie, etc. In our previous work [16], we showed that, by using three images, we are able to recover the location of an object moving in a direction parallel to the motion of the camera. In this research, we will show that, by using four images, we are able to recover the location of an object moving linearly in an arbitrary direction.  
This paper is organized as follows. Section 2 reviews the related works in object localization. The system design of our proposed method is described in Section 3, and the mathematical formulation is discussed in Section 4. Section 5 gives the implementation details and Section 6 shows the evaluation performance of the proposed method. Finally, Section 7 provides some discussion on the localization errors, and Section 8 gives the conclusion and a summary of our proposed approach.