Advanced search options

Advanced Search Options 🞨

Browse by author name (“Author name starts with…”).

Find ETDs with:

in
/  
in
/  
in
/  
in

Written in Published in Earliest date Latest date

Sorted by

Results per page:

Sorted by: relevance · author · university · dateNew search

You searched for +publisher:"University of Illinois – Chicago" +contributor:("Radakovic, Daniela"). Showing records 1 – 3 of 3 total matches.

Search Limiters

Last 2 Years | English Only

No search limiters apply to these results.

▼ Search Limiters


University of Illinois – Chicago

1. Manavella, Andrea. Traffic Light Detection for Portable Assistive Device to Aid Blind Pedestrians.

Degree: 2015, University of Illinois – Chicago

Automated traffic light recognition is a key technology of interest in applications involving autonomous vehicles and safe driving. There are other important applications such asassistive technology for visually impaired pedestrians w he re traffic recognition is relevant. Crossing streets and navigating in crowded environments like cities can b e very hard for the significant segment of population that is blind or visually impaired. In the past few years, several research efforts were undertaken and papers published on regular traffic light detection. Some attempts have been made to detect traffic light signals but a comprehensive method still has to b e develop ed. The main goal of the work in this thesis was to develop technology to b e integrated in a simple wearable device for blind people to help them navigate outdoors to perform their everyday life activities and in particular to cross streets safely. The problem of automated traffic light in the absence of infrastructure is addressed. The proposed method examined various alternatives and an algorithm was devised to detect traffic lights by first selecting possible candidates by performing traffic light color extraction, pruning the large candidate set using traffic light properties, next carrying out recognition and classification of lights before finally making a decision on the traffic light signal. When tested on a set of image data, the algorithm achieved go o d results with the estimated correct detection rate of the prototype determined to b e above 90 %. The detection of pedestrian traffic signals indicating “walk and don't walk" was also considered and the algorithm devised for this problem also yielde d go o d results, again with an estimated correct detection rate better than 90 % Advisors/Committee Members: Ansari, Rashid (advisor), Radakovic, Daniela (committee member), Passerone, Claudio (committee member).

Subjects/Keywords: traffic light recognition; blind aid; machine learning

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Manavella, A. (2015). Traffic Light Detection for Portable Assistive Device to Aid Blind Pedestrians. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/19463

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Manavella, Andrea. “Traffic Light Detection for Portable Assistive Device to Aid Blind Pedestrians.” 2015. Thesis, University of Illinois – Chicago. Accessed March 02, 2021. http://hdl.handle.net/10027/19463.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Manavella, Andrea. “Traffic Light Detection for Portable Assistive Device to Aid Blind Pedestrians.” 2015. Web. 02 Mar 2021.

Vancouver:

Manavella A. Traffic Light Detection for Portable Assistive Device to Aid Blind Pedestrians. [Internet] [Thesis]. University of Illinois – Chicago; 2015. [cited 2021 Mar 02]. Available from: http://hdl.handle.net/10027/19463.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Manavella A. Traffic Light Detection for Portable Assistive Device to Aid Blind Pedestrians. [Thesis]. University of Illinois – Chicago; 2015. Available from: http://hdl.handle.net/10027/19463

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Illinois – Chicago

2. Mercurio, Cesare. Automated Real-Time Tracking System for Blood Vessels of the Eye.

Degree: 2015, University of Illinois – Chicago

The Eye tracking is a very hot topic and in the past few years, not-invasive methods have been introduced thank to the development of new image processing and computer vision techniques. Most of them are based on optical-tracking, which means that the tracking of the eye is performed by using infrared light and complex optics to measure the corneal reflection of the light, taking also into account the shifts of the center of the pupil over the time. A new not-invasive approach to this problem is described in this the sis, in which the purpose is to have a video with fixed images that allows the measurement of the conjunctiva blood vessel diameter and blood velocity. Therefore, the area of interest of the eye is the region of the blood vessels. The main idea of the new approach is to make the camera seeing always the same blood vessels area and performing a cross-correlation algorithm in order to track the movement of the patients eye. Depending on the system and the resources available, this algorithm could consider the whole image or a specific pattern such as the vessels intersection. The main goal is to reduce the usage of the registration algorithm as post-processing technique in order to build a video with fixed and stable images of the region of interest. Advisors/Committee Members: Ansari, Rashid (advisor), Radakovic, Daniela (committee member), Shahidi, Mahnaz (committee member).

Subjects/Keywords: Real-Time; Image processing; Tracking System; computer vision

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Mercurio, C. (2015). Automated Real-Time Tracking System for Blood Vessels of the Eye. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/19464

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Mercurio, Cesare. “Automated Real-Time Tracking System for Blood Vessels of the Eye.” 2015. Thesis, University of Illinois – Chicago. Accessed March 02, 2021. http://hdl.handle.net/10027/19464.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Mercurio, Cesare. “Automated Real-Time Tracking System for Blood Vessels of the Eye.” 2015. Web. 02 Mar 2021.

Vancouver:

Mercurio C. Automated Real-Time Tracking System for Blood Vessels of the Eye. [Internet] [Thesis]. University of Illinois – Chicago; 2015. [cited 2021 Mar 02]. Available from: http://hdl.handle.net/10027/19464.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Mercurio C. Automated Real-Time Tracking System for Blood Vessels of the Eye. [Thesis]. University of Illinois – Chicago; 2015. Available from: http://hdl.handle.net/10027/19464

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

3. Valsesia, Diego. Multiple Description Coding for Distributed Compressed Sensing.

Degree: 2013, University of Illinois – Chicago

The following thesis is devoted to the study of a multiple description framework for compressed sensing, with particular focus on a distributed application of compressed sensing. Compressed sensing is a novel theory for signal acquisition, that enables to directly acquire a compressed representation of a sparse or compressible signal, regardless of what is the basis in which the signal is actually sparse (compressible). The low complexity of an acquisition stage adopting compressed sensing raised interests about adopting it in sensor networks. In this distributed scenario compressed sensing is also able to exploit inter-correlation, in the form of joint sparsity, among different signals to improve coding efficiency without demanding any complex operation. Our work proposes the CS-SPLIT scheme to generate two or more descriptions from measurements acquired through compressed sensing. This scheme proved experimentally superior to another classic method of obtaining multiple descriptions, that is using a multiple description scalar quantizer on the measurements (CS-MDSQ). An analytic treatment of the two methods in terms of rate-distortion performance has also been given, using the current results in the theory of compressed sensing. CS-SPLIT can be readily used in sensor networks thanks to its extreme simplicity. We developed two new joint reconstruction algorithms (Difference and Texas Difference) that significantly improve over existing algorithms for the JSM-1 model, when the number of measurements is limited. This is relevant to multiple descriptions because it allows to get a better quality in the reconstruction of the single descriptions of CS-SPLIT when joint decoding is not possible. Advisors/Committee Members: Ansari, Rashid (advisor), Radakovic, Daniela (committee member), Magli, Enrico (committee member).

Subjects/Keywords: compressed sensing; multiple description coding

Page 1 Page 2 Page 3 Page 4 Page 5 Page 6 Page 7

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Valsesia, D. (2013). Multiple Description Coding for Distributed Compressed Sensing. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10027/9925

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Valsesia, Diego. “Multiple Description Coding for Distributed Compressed Sensing.” 2013. Thesis, University of Illinois – Chicago. Accessed March 02, 2021. http://hdl.handle.net/10027/9925.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Valsesia, Diego. “Multiple Description Coding for Distributed Compressed Sensing.” 2013. Web. 02 Mar 2021.

Vancouver:

Valsesia D. Multiple Description Coding for Distributed Compressed Sensing. [Internet] [Thesis]. University of Illinois – Chicago; 2013. [cited 2021 Mar 02]. Available from: http://hdl.handle.net/10027/9925.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Valsesia D. Multiple Description Coding for Distributed Compressed Sensing. [Thesis]. University of Illinois – Chicago; 2013. Available from: http://hdl.handle.net/10027/9925

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.