Current teaching schedule:
Course descriptions:
  •  EK131-132: “Introduction to Engineering: From heart monitoring to Kinect gaming: Seeing the invisible” (introductory course for freshmen)
    Did you ever wonder how a physician measures your heartbeat or other vital signs, a submarine identifies underwater obstacles or your Xbox and Kinect seem to recognize you and your every move? Your beating heart, a rock 300m underwater and your skeleton are not visible to a naked eye, so how can these invisible signals be measured? This course will explain how this is accomplished and, in the process, will introduce you to the world of signals, their processing and some exciting applications. This is a hands-on course; lectures will be combined with team exercises involving a variety of sensors. For example, you will experiment with a heart monitor app on your smartphone, you will build your own sonar to measure distance to objects using sound, and you will design an interface to control your computer with gestures instead of mouse/keyboard. The course will culminate with an exciting team project involving Microsoft Kinect.
  • EC401 “Signals and Systems”
    This course introduces mathematical apparatus needed to analyze, capture, manipulate and use various physical phenomena observed in real world, such as temperature, pressure, sound, light, etc. This can be accomplished entirely in the analog (continuous) domain, e.g., turning off a room heater once a preset temperature has been reached (bimetallic switch), but flexibility of analog systems is limited. This is different when a physical signal is captured and digitized for manipulation by a digital processor – a wide range of operations can be implemented in a computer language (much more than just checking temperature value). The digital manipulation of signals gave rise in recent decades to a wealth of new consumer services (cellular telephony, audio and video streaming, GPS navigation) and devices (digital cameras, smartphones, smart speakers), but also had a huge impact on professional markets (automotive, medical diagnostics, remote sensing, surveillance). The success of digital signal manipulation stems from its versatility (many digital operations have no analog counterpart), flexibility (algorithms can be easily changed in software) and cost (advances in VLSI). This course will introduce students to both analog and digital signals, and show their many practical applications.
  •  EC416 “Introduction to Digital Signal Processing” (technical elective for juniors or seniors)
    The goal of this course is to introduce basic concepts and methods of digital signal processing (DSP), i.e., digital processing of analog signals. DSP plays a very important role in modern communications (wired and mobile), consumer electronics (CD, MD, MP3 players), entertainment (DVD, DV, DTV, HDTV, digital cinema) and professional (medical imaging, remote sensing) markets. The success of DSP in those markets stems from its versatility (many DSP operations have no analog counterpart), flexibility (algorithms can be easily changed through firmware upgrade) and cost (continuing advances in VLSI). The course introduces techniques of digital signal processing and application to deterministic as well as random signals. Topics include representation of discrete-time random signals, A/D conversion, D/A conversion, frequency domain and z-domain analysis of discrete-time signals and systems, discrete-time feedback systems, difference equation and FFT-based realization of digital filters, design of IIR Butterworth filters, window-based FIR filter design, digital filtering of random signals, FFT-based power spectrum analysis.
  •  EC520: “Digital Image Processing and Communication” (mezzanine graduate course)
    The goal of this course is to provide the theoretical and practical basis required for the understanding and design of modern image processing and image communication systems. The material covered in the course will primarily concentrate on still images but will also relate certain concepts from digital video (image sequences). The course will be organized in such a way that students can master background needed for research in image-related areas and simultaneously acquire in-depth understanding of modern applications of image processing, e.g., storage and transmission of images and video (wireless, Internet), digital photography.
  •  EC720: “Digital Video Processing” (advanced graduate course)
    This is an advanced graduate course extending EC520 (“Digital image processing and communication”) to dynamic imagery, i.e., digital video and other image sequences. The goal of this course is to provide the understanding of the theory behind various video processing tasks as well as practical experience in simulating them. The material covered in the course will extend numerous concepts from still (2-D, i.e., x-y) images to dynamic imagery (3-D, i.e., x-y-t), but will also introduce new concepts unique to spatio-temporal data such as timeline, motion, occlusions, etc. The course format will be a combination of regular lectures and homework assignments, and of compulsory readings followed by in-class discussions. A very important aspect of the course will be a practical project. Students will select a topic, find suitable literature (with instructor’s guidance) and carry out a simulation in Matlab and/or C/C++. Upon the completion of this course students will have acquired in-depth knowledge to carry out research in image sequence-related areas and also an understanding of modern applications of video processing (e.g., digital video – miniDV, HDTV, MPEG-2, MPEG-4, streaming video over Internet).
Project outcomes:

Below are videos describing outcomes of some recent course projects. Detailed project descriptions can be found in project reports further below.

Project Reports

N. K. Hannesdottir, C. Hunter, and K. Vogt-Lowell, “Detection and classification of artistic styles in photographed artwork using deep learning,” Tech. Rep. 2022-03, Boston University, Dept. of Electr. and Comp. Eng., May 2022 (EC520 course project).

L. Ivey and P. Hutchinson Maltaghati, “Suspicious vehicle detection,” Tech. Rep. 2022-02, Boston University, Dept. of Electr. and Comp. Eng., May 2022 (EC520 course project).

C. Cipriano and M. Housego, “Depth-driven computational imaging: Portrait mode and privacy filter leveraging focal stack and point cloud data,” Tech. Rep. 2022-01, Boston University, Dept. of Electr. and Comp. Eng., May 2022 (EC520 course project).

L. Le and H. Nguyen, “Image forgery detection using color-correlation analysis or convolutional neural networks,” Tech. Rep. 2021-02, Boston University, Dept. of Electr. and Comp. Eng., May 2021 (EC520 course project).

K. Wooldridge and G. Yap, “Depth-driven augmented reality,” Tech. Rep. 2021-01, Boston University, Dept. of Electr. and Comp. Eng., Apr. 2021 (EC520 course project).

Z. Duan and X. Liang, “Video instance segmentation,” Tech. Rep. 2019-04, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2019 (EC720 course project).

Y. Xiao and X. Lin, “Fall detection using low-resolution thermal sensor,” Tech. Rep. 2019-03, Boston University, Dept. of Electr. and Comp. Eng., May 2019 (EC520 course project).

Y.-S. Park and J. Warren, “Hand-gesture recognition using Kinect,” Tech. Rep. 2019-02, Boston University, Dept. of Electr. and Comp. Eng., May 2019 (EC520 course project).

E. Babbitt and N. Catell, “Still-image copy detection,” Tech. Rep. 2019-01, Boston University, Dept. of Electr. and Comp. Eng., May 2019 (EC520 course project).

Y. Xue and C. Yurdakul, “People counting using overhead panoramic camera,” Tech. Rep. 2018-03, Boston University, Dept. of Electr. and Comp. Eng., Aug. 2018 (EC520 course project).

S. Werth and A. Matlock, “Neural network-based microscope defocus correction with point spread,” Tech. Rep. 2018-02, Boston University, Dept. of Electr. and Comp. Eng., Aug. 2018 (EC520 course project).

M. O. Tezcan, “Motion estimation using convolutional neural networks,” Tech. Rep. 2017-04, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2017 (EC720 course project).

J. Intoy and E. Lam, “Room occupancy sensing using a thermal tripwire,” Tech. Rep. 2017-03, Boston University, Dept. of Electr. and Comp. Eng., July 2017 (EC520 course project).

P. Yuan and M. Brawley, “Outlier color detection for search and rescue applications,” Tech. Rep. 2017-02, Boston University, Dept. of Electr. and Comp. Eng., May 2017 (EC520 course project).

S. Sharma and N. Bose, “Activity recognition from single-pixel cameras,” Tech. Rep. 2015-07, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2015 (EC720 course project).

D. Lavy and T. Marshall, “Autonomous navigation with NAO,” Tech. Rep. 2015-06, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2015 (EC720 course project).

L. N. Perkins, “Convolutional neural networks as feature generators for near-duplicate video detection,” Tech. Rep. 2015-05, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2015 (EC720 course project).

D. Lavy and D. Pham, “Virtual shape recognition using Leap Motion,” Tech. Rep. 2015-03, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2015 (EC520 course project).

J. Rapp, S. Welch, and S. Kumaresan, “Example-based image retrieval,” Tech. Rep. 2015-02, Boston University, Dept. of Electr. and Comp. Eng., May 2015 (EC520 course project).

T. Marshall and L. N. Perkins, “Color outlier detection for search and rescue,” Tech. Rep. 2015-01, Boston University, Dept. of Electr. and Comp. Eng., May 2015 (EC520 course project).

C. Chan and S. S. Mirfakhraei, “Hand gesture control using Kinect,” Tech. Rep. 2013-04, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2013 (EC520 course project).

M. Ramachandran and W. Moik, “Outlier color identification for search and rescue,” Tech. Rep. 2013-03, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2013 (EC520 course project).

T. Bolukbasi and P. Tran, “Outlier color identification for search and rescue,” Tech. Rep. 2012-07, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2012 (EC520 course project).

A. Gaudreau-Balderrama, “Multi-modal image registration,” Tech. Rep. 2012-04, Boston University, Dept. of Electr. and Comp. Eng., May 2012 (EC720 course project).

J. Wu, “Saliency detection in video,” Tech. Rep. 2012-04, Boston University, Dept. of Electr. and Comp. Eng., May 2012 (EC720 course project).

L. Ross and M. Crane, “Video analytics in a retail environment,” Tech. Rep. 2012-02, Boston University, Dept. of Electr. and Comp. Eng., May 2012 (EC720 course project).

G. P. Prince and P. Butala, “Video analytics for retail environment,” Tech. Rep. 2012-01, Boston University, Dept. of Electr. and Comp. Eng., May 2012 (EC720 course project).

H. Du and T. To, “Hand gesture recognition using Kinect,” Tech. Rep. 2011-04, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2011 (EC520 course project).

J. Wu, “Face recognition jammer using image morphing,” Tech. Rep. 2011-03, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2011 (EC520 course project).

L. C. Campos and G. P. Prince, “Visual sensor for smart parking,” Tech. Rep. 2011-02, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2011 (EC520 course project).

A. Macdonell and J. Lobo, “Visual sensor for smart parking,” Tech. Rep. 2011-01, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2011 (EC520 course project).

H. Wu and Y. Yu, “Real-time background subtraction in C++,” Tech. Rep. 2010-06, Boston University, Dept. of Electr. and Comp. Eng., May 2010 (EC720 course project).

M. Wang and Y. Shao, “The Google challenge: Video genre classification,” Tech. Rep. 2010-05, Boston University, Dept. of Electr. and Comp. Eng., May 2010 (EC720 course project).

E. Choi Loya Zorn and L. Ravindranathan, “Motion filtering: A frequency-domain approach,” Tech. Rep. 2010-04, Boston University, Dept. of Electr. and Comp. Eng., May 2010 (EC720 course project).

J. Fu and V. Ruiz Albacete, “Motion filtering in space-time,” Tech. Rep. 2010-03, Boston University, Dept. of Electr. and Comp. Eng., May 2010 (EC720 course project).

M. De Paolis Kaluza and S. Poomcharoenwatana, “Content-aware video-frames resizing using seam carving,” Tech. Rep. 2009-07, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2009 (EC520 course project).

Y. Pan and S. Zeng, “Content-aware video frame decimation,” Tech. Rep. 2009-06, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2009(EC520 course project).

S. Bakr, “Detection of motor vehicles and humans on ocean shoreline,” Tech. Rep. 2009-05, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2009 (EC520 course project).

E. Zorn and L. Amarnath, “Color-based classification of colonoscopy video frames,” Tech. Rep. 2009-04, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2009 (EC520 course project).

J. Lin and X. Lu, “Discovery of camera network topology,” Tech. Rep. 2008-06, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2008 (EC520 course project).

B. Abanoz and M. Wang, “A review of high dynamic range imaging on static scenes,” Tech. Rep. 2008-04, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2008 (EC520 course project).

H. Ozkan and J. Tang, “Camera jitter compensation,” Tech. Rep. 2008-02, Boston University, Dept. of Electr. and Comp. Eng., May 2008 (EC720 course project).

D. Mabius and J. Tang, “Omnidirectional imaging,” Tech. Rep. 2007-07, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2007 (EC520 course project).

K. Guo and Z. Li, “Image reconstruction from omni-directional camera,” Tech. Rep. 2007-06, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2007 (EC520 course project).

C. Ren and W. Lin, “Crab counter,” Tech. Rep. 2007-05, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2007 (EC520 course project).

W. Liu and K. Chen, “Crab counter,” Tech. Rep. 2007-04, Boston University, Dept. of Electr. and Comp. Eng., Dec. 2007 (EC520 course project).