This course gives a broad overview of the field of computer vision, laying the foundations for advanced graduate level classes and research work in vision. This course will be conducted with an application perspective. Therefore students will be expected to implement several techniques learnt in the lectures. A good calculus, linear algebra and programming background…
Deep Learning is a hierarchical learning methodology based on artificial neural networks which are algorithms inspired by the structure and function of the brain. It has applications in wide-range of industries these days such as face-recognisers working at massive scales, robotics, speech translation, text analysis, improving customer experience, autonomous vehicles etc. In this course we…
Omair Hassaan, Abeera Shamail, Zain Butt, Murtaza Taj The 25th Pacific Conference on Computer Graphics and Applications (Pacific Graphics 2017), Taipei, Taiwan, Oct 16 – 19, 2017 Abstract Recent advancements in 3D scanning technologies have paved way for generation of highly accurate 3D scenes in the form of point cloud data. For the segmentation and…
Reema Bajwa, Syed Rizwan Gilani, Murtaza Taj Short Paper Proceedings of the 33rd Computer Graphics International, Heraklion, Greece, June 28 – July 1, 2016 Abstract We present a coarse-to-fine model fitting approach that automatically generates a detailed CAD like model from a point cloud. We first developed a library of detailed parametric models for each…
Ahsan Abdullah, Reema Bajwa, Syed Rizwan Gilani, Zuha Agha, Saeed Boor Boor, Murtaza Taj, Sohaib Ahmed Khan The 36th Annual Conference of the European Association for Computer Graphics, 2015 Kongresshaus in Zürich, Switzerland, 4th – 8th May, 2015 Abstract We present a modeling approach to automatically fit 3D primitives to point clouds in order to…
More information: Video | PDF Text Reference: Ali Hassan and Murtaza Taj, “2D articulated human pose tracking: A hybrid approach”, IEEE International Conference on Image Processing (ICIP), 2014 Bibtex Reference: @inproceedings{ResNet3DLeakyReLU2019, author = “Ali Hassan and Murtaza Taj”, title = “2D articulated human pose tracking: A hybrid approach”, booktitle = “IEEE International Conference on…
Murtaza Taj, Andrea Cavallaro International Conference on Image Processing, ICIP 2012 Abstract We present an event recognition framework to detect interactions among objects, for example people, using a network of cameras and associated microphone pairs. The complementarity of the video and audio modalities is exploited to cover wide areas. In particular, object movements in portions of the scene that…
Murtaza Taj, Andrea Cavallaro IEEE Signal Processing Magazine, 2011 Abstract In recent years the decreasing cost of cameras and advances in miniaturization have favoured the deployment of largescale camera networks. This growing number of cameras enables new signal processing applications that use cooperatively multiple sensors over wide areas. In particular, object tracking is an important…
Fahad Daniyal, Murtaza Taj, Andrea Cavallaro Multimedia Tools and Applications, 2009 Abstract We present a content-aware multi-camera selection technique that uses object and frame-level features. First objects are detected using a color-based change detector. Next trajectory information for each object is generated using multi-frame graph matching. Finally, multiple features including size and location are used…
Huiyu Zhou, Murtaza Taj, Andrea Cavallaro IEEE Journal of Selected Topics in Signal Processing, 2008 Abstract We present a multimodal detection and tracking algorithm for sensors composed of a camera mounted between two microphones. Target localization is performed on color-based change detection in the video modality and on Time Difference of Arrival (TDOA) estimation between…
