Vision algorithms for Emerging Applications

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Video surveillance represents one of the fastest growing industries in Canada and the world. It is estimated that the revenue will be $15.9 billion in 2014 compared $14.1 billion in 2013. Terrorism and high crime rates in our societies demand more efficient surveillance systems. With the recent advances in imagery sensor technology and aerial vehicles, aerial surveillance has become a very active area, especially with the introduction of Wide Area Motion Imagery (WAMI) in 2007. At the core of these surveillance systems are object detection, tracking, and activity recognition.***This research program investigates the design and development of advanced techniques for object detection and tracking in wide area motion imagery (WAMI); specifically, we will investigate the following three research themes: 3D aerial reconstruction, stabilization and object detection, and object tracking.****In the area of 3D aerial reconstruction, we will design and develop new algorithms that formulate the problem differently from the traditional disparity based algorithms and use dense matching and global optimization techniques.***In the area of stabilization and object detection, we will design and develop a new robust stabilization technique such that we can treat the outliers in the images that did not follow the transformation function from the stabilization as candidate target objects. We will focus on addressing and minimizing the parallax and ghost effects. ***In the area of object tracking, a recent study in 2014 compared the performance of different trackers in WAMI and concluded that the best performance accuracy achieved was 70%. This is due to high altitude and small object size in cluttered scenes, especially in high density motion areas with large number of objects. We will design new algorithms that represent the objects in higher dimensional feature vectors based on selected filter responses. ***The proposed algorithms will be analyzed using both analytical and experimental methods. The algorithms will be tested on Columbus Large Image Format (CLIF) and VIVID datasets, and also by using aerial vehicles to demonstrate real-time performance. ***This research program will help create new innovative aerial surveillance systems that can be used in the industry of Wide Area Arial Surveillance (WAAS), which is one of the emerging technologies that provide surveillance coverage in city-size coverage. ***This research program will also provide training to 20-25 undergraduate and graduate students in total helping them build strong backgrounds in advanced topics in image processing, computer vision, digital signal processing, optimization, information theory, and computational complexity analysis. The students will gain hands-on experience by performing experimental work using state-of-the-art vision equipment and software tools and implementing the algorithms on constrained resources embedded boards.**