The Early Prototype Proposal is designed to help students explore potential project topics and form the right groups. In this proposal, each student should outline their initial project idea and express their interest in the listed papers. Focus on summarizing your project at a high level, avoiding technical details. The goal of this proposal is to communicate your interests and project ideas to facilitate group formation. Students can change their topics as the project progresses. Submitted proposals will be published on the course website and shared with other students. Feel free to reach out to classmates who share similar ideas to form a group.
Deadline September 29th, 2024: Submission Link
The Early Prototype Proposal must include the following:
Student Name
NetID
Project Type (choose from IMU/Audio/Image/Video)
Abstract (no more than 500 characters)
Student Name: Thomas Moon
NetID: tmoon
Project Type (choose from IMU/Audio/Image/Video): IMU
Abstract: This project will focus on using IMU sensors to track and log a user’s exercise movements. One or more IMU sensors will be used to detect and classify the motion of a tablet during exercise. The goal is to implement a basic machine learning algorithm, leveraging DSP techniques, to improve the accuracy of movement tracking and classification.
Below is a list of widely used and popular DSP algorithms commonly implemented in real-time DSP systems. Students are also welcome to choose papers or topics outside of this list. If you select a topic not included in the list, you are required to consult with the teaching staff.
Wang, Avery. "An industrial strength audio search algorithm." Ismir. Vol. 2003. 2003.
Cooper, Matthew, and Jonathan Foote. "Automatic Music Summarization via Similarity Analysis." ISMIR. 2002.
Pradhan, Swadhin, et al. "Smartphone-based acoustic indoor space mapping." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2.2 (2018): 1-26.
Graham, Daniel, et al. "A software-based sonar ranging sensor for smart phones." IEEE Internet of Things Journal 2.6 (2015): 479-489.
Rafii, Zafar, and Bryan Pardo. "Repeating pattern extraction technique (REPET): A simple method for music/voice separation." IEEE transactions on audio, speech, and language processing 21.1 (2012): 73-84.
Ellis, Daniel PW, and Bertin-Mahieux Thierry. "Large-scale cover song recognition using the 2d fourier transform magnitude." (2012): 241-246.
Hansen, John HL, and Taufiq Hasan. "Speaker recognition by machines and humans: A tutorial review." IEEE Signal processing magazine 32.6 (2015): 74-99.
Ballard, Dana H. "Generalizing the Hough transform to detect arbitrary shapes." Pattern recognition 13.2 (1981): 111-122.
Matthew Turk and Alex Pentland, "Eigenfaces for Recognition." Journal of Cognitive Neuroscience 1991 3:1, 71-86
Belhumeur, Peter N., Joao P. Hespanha, P. Hespanha, and David J. Kriegman. "Eigenfaces vs. fisherfaces: Recognition using class specific linear projection." IEEE Transactions on pattern analysis and machine intelligence 19.7 (1997): 711-720.
Wagner, Andrew, et al. "Toward a practical face recognition system: Robust alignment and illumination by sparse representation." IEEE transactions on pattern analysis and machine intelligence 34.2 (2011): 372-386.
Butler, Darren E., V. Michael Bove, and Sridha Sridharan. "Real-time adaptive foreground/background segmentation." EURASIP Journal on Advances in Signal Processing 2005.14 (2005): 1-13.
Lowe, David G. "Object recognition from local scale-invariant features." Computer vision, 1999. The proceedings of the seventh IEEE international conference on. Vol. 2. Ieee, 1999.
S. Baker and I. Matthews, "Lucas-Kanade 20 years on: A unifying framework." International Journal of Computer Vision, vol. 56, no. 3, pp. 221-255, Mar. 2004.
Matthews, Iain, et al. "Extraction of visual features for lipreading." IEEE Transactions on Pattern Analysis and Machine Intelligence 24.2 (2002): 198-213.
Achanta, Radhakrishna, et al. "SLIC superpixels compared to state-of-the-art superpixel methods." IEEE transactions on pattern analysis and machine intelligence 34.11 (2012): 2274-2282.
Zitnick, C. Lawrence, and Piotr Dollár. "Edge boxes: Locating object proposals from edges." European conference on computer vision. Faller, Cham, 2014.
Yan, Qiong, et al. "Hierarchical saliency detection." Proceedings of the IEEE conference on computer vision and pattern recognition. 2013.
Cho, Sunghyun, Jue Wang, and Seungyong Lee. "Video deblurring for hand-held cameras using patch-based synthesis." ACM Transactions on Graphics (TOG) 31.4 (2012): 1-9.