Rohan C. Loveland

Camera distortion self-calibration using the plumb-line constraint and minimal Hough entropy

In this paper, we present a simple and robust method for self-correction of camera distortion using single images of scenes which contain straight lines. Since the most common distortion can be modelled as radial distortion, we illustrate the method using the Harris radial distortion model, but the method is applicable to any distortion model. The method is based on transforming the edgels of the distorted image to a 1-D angular Hough space, and optimizing the distortion correction parameters which minimize the entropy of the corresponding normalized histogram. Properly corrected imagery will have fewer curved lines, and therefore less spread in Hough space. Since the method does not rely on any image structure beyond the existence of edgels sharing some common orientations and does not use edge fitting, it is applicable to a wide variety of image types. For instance, it can be applied equally well to images of texture with weak but dominant orientations, or images with strong vanishing points. Finally, the method is performed on both synthetic and real data revealing that it is particularly robust to noise.

Comparison of methods of determining meteoroid range rates from linear frequency modulated chirped pulses

[1] In this paper we present three methods for evaluating range rates of meteoroids passing through the ionosphere, using linear frequency modulated (LFM) chirped pulse data from the ALTAIR radar. The first method is based on the simple calculation of range differences divided by interpulse intervals. The second method utilizes the dual‐frequency capability of ALTAIR to solve for range rates based on the difference in the measured ranges due to range‐Doppler coupling. The third method utilizes a simplified form of integer programming in order to unwrap the phase differences of the matched filter time response, with reliance on the rough approximation available from the first method to disambiguate the solution set. The results of the three methods, with error bounds, are given for a large set of meteoroid head echoes taken from a data collection conducted with ALTAIR in 2007. Citation: Loveland, R., A. Macdonell, S. Close, M. Oppenheim, and P. Colestock (2011), Comparison of methods of determining meteoroid range rates from linear frequency modulated chirped pulses, Radio Sci., 46, RS2007,

Building robust appearance models using on-line feature selection

In many tracking applications, adapting the target appearance model over time can improve performance. This approach is most popular in high frame rate video applications where latent variables, related to the objects appearance (e.g., orientation and pose), vary slowly from one frame to the next. In these cases the appearance model and the tracking system are tightly integrated, and latent variables are often included as part of the tracking systems dynamic model. In this paper we describe our efforts to track cars in low frame rate data (1 frame / second), acquired from a highly unstable airborne platform. Due to the low frame rate, and poor image quality, the appearance of a particular vehicle varies greatly from one frame to the next. This leads us to a different problem: how can we build the best appearance model from all instances of a vehicle we have seen so far. The best appearance model should maximize the future performance of the tracking system, and maximize the chances of reacquiring the vehicle once it leaves the field of view. We propose an online feature selection approach to this problem and investigate the performance and computational trade-offs with a real-world dataset.

Acquisition and registration of aerial video imagery of urban traffic

The amount of information available about urban traffic from aerial video imagery is extremely high. Here we discuss the collection of such video imagery from a helicopter platform with a low-cost sensor, and the post-processing used to correct radial distortion in the data and register it. The radial distortion correction is accomplished using a Harris model. The registration is implemented in a two-step process, using a globally applied polyprojective correction model followed by a fine scale local displacement field adjustment. The resulting cleaned-up data is sufficiently well-registered to allow subsequent straight-forward vehicle tracking.