MSc dissertation proposal 2015/2016

Scheduled Gigapixel Sensing and Multi-Target Tracking

Introduction:

Gigapixel cameras have been recently tested in the DARPA AWARE program. Their extremely high resolution, comparable to the best of the human eye, is certainly advantageous for many applications. However, it also means complex optics, electronics, communications and processing software, surely not within the budget of many law enforcement, industrial users or other civilian applications.

Alternatively, one has nowadays pan-tilt-zoom cameras, which provide gigapixel-like resolution for a point of interest. They just do not provide omni-awareness. Nevertheless, one can reason whether an efficient scheduling of points of interest can be a mitigating factor, much as the motion of the human eye allows tracking in high (foveal) resolution on the surface of an egosphere. This is the central aspect of this project.

Objectives:

The project is based in the research and development of two fundamental components: (i) camera modeling and calibration and (ii) vision based target tracking.

Detailed Description:

The scenario for this work is a urban environment observed by a number of pan-tilt-zoom cameras. The cameras work in a cooperative manner to track a number of targets (e.g. vehicles or people).

The main tasks of the project are the following:

1. Acquisition of Panoramic Video Datasets - Build video datasets with panoramic views that allow simulating up to some extent the pan and tilt movements of PTZ cameras.

2. Camera Calibration - We consider in essence pan-tilt-zoom and omnidirectional cameras, and develop geometric and radiometric models for these cameras. In a first approach, calibration is achieved using calibration patterns and, in a second instance, in natural features of a scene. Calibration may involve both types of cameras working cooperatively in the same network.

3. Active Camera Management for Multitarget Tracking - Assess the capability of Switched Linear Dynamic Models (SLDM) for the online prediction of tracking targets dynamics, and then develop an active camera management policy based in the information theory framework.

References:

[Micheloni10] "Video Analysis in Pan-Tilt-Zoom Camera Networks: From master-slave to cooperative smart cameras", Christian Micheloni, Bernhard Rinner, and Gian Luca Foresti, IEEE Signal Processing Magazine September 2010

Expected Results:

The student will develop skills in computer vision and signal filtering. The final result must consist of in the demonstration of an application illustrating the successful achievement of the theoretical and practical aspects of the work.

-- More information in:

http://users.isr.ist.utl.pt/~jag/msc/msc_2015_2016.html

More MSc dissertation proposals on Computer and Robot Vision in:

http://omni.isr.ist.utl.pt/~jag