The iCVL offers various senior projects for teams of students in Computer Science (marked CS) or Software Engineering (marked SE). The list below is kept up to date and always contains projects that are open. Ongoing projects are listed separated at the bottom of the page.
Augmented reality Geo-locator app (CS,SE)
How often does it happen to you that you scan the scenery, observe far urban or rural settlements from a distance but do not know to name them? In this project we will develop a mobile app that solves this problem by endowing the reality observed by the smart device with proper geographical labels while taking into consideration visibility constraints. Additional features over the basic capacity will be considered during the project. For details please contact: Prof. Ohad Ben-Shahar.
Robotic polygonal puzzle solver (CS,SE)
Th iCVL lab has been pushing the abilities to solve visual puzzles to new fronts, including implementations of robotic puzzle solving for what is known as “square puzzles” (puzzles of square pieces). In this project will explore the automatic acquisition and solution of simple physical polygonal puzzles, bringing us closer to real life applications like archeology (where pieces rarely are square) . For details please contact: Prof. Ohad Ben-Shahar.
Eye movements in the wild (CS)
Humans execute rapid eye movements between locations well over 100,000 times a day. These movements are an integral part of our visual system, used for acquiring relevant information, tracking visual targets, and allowing us to function properly in our world. Tracking eye-movements and measuring how they change in response to different visual stimuli provide a window into human visual perception. Recent portable eye-tracking technology allows to measure eye movements under natural conditions. Most research based on this technology explores the nature of the visual system when it is bound to a specific and explicit task (e.g., driving, walking or preparing food). But what could eye-movements tell us about the visual system when it is independent of any specific or explicit task? In order to answer this question, we will measure human eye-movement behavior under free viewing conditions in the outdoors using goggles with eye tracking capacities. By analyzing the measurements, we will explore several issues related to the function of the human visual system under natural conditions and will seek for ways to incorporate this knowledge into artificial visual systems. For example, we will ask whether or not the bias to move our eyes to the center of the visual field persist even when the head moves freely and the the retinal image changes continuously. Several different projects may be available under this topic. For details please contact: Mr. Rotem Mairon or Prof. Ohad Ben-Shahar.
A scale-space representation for eye movement scan paths (CS)
As mentioned above, humans execute rapid eye movements between locations well over 100,000 times a day. These movements consist of transitions of many different amplitudes and directions, grossly classified as fixational eye movements and saccades, and most eye trackers indeed apply this classification in a proprietary fashion. In this research project we will build a system and a GUI that allows to present and study the raw scan paths more closely, and in particular, to overide the eye tracker’s decision making in a parametric way, seeking (what may be called) a scale-space representation for scan path. For details please contact: Prof. Ohad Ben-Shahar.
Mobile Gazer – A mobile phone eye tracker (CS)
Tracking gaze is now ubiquitous and various eye trackers are available in different forms, including head mounted trackers, remote trackers, and even portable trackers mounted on glasses. In this project we will seek to develop a portable remote eye tracker on a smartphone such that one’s gaze can be monitored while using the phone. Such a capacity, implemented with the phone’s front camera, can then be used for multitude of applications, from entertainment (gaming), through biometrics, to assisting the handicapped and we will explore at least one such application in the projects too. Smartphone programming or computer vision skills are a plus but not mandatory. For details please contact: Prof. Ohad Ben-Shahar.
Hyperspectral vision (CS)
While color vision allows humans and other primates to see the world in amazing detail, light in the visible spectrum carries more information than just “Red, green and blue”, advanced “Hyperspectral” cameras allow us to explore the would around us in greater detail revealing the hidden colors that lie beyond the capabilities of human vision. In this project we will use advanced hyperspectral imaging equipment to observe natural scenes and study their properties. Several different different projects may be available under this topic, from. For details please contact: Mr. Boaz Arad or Prof. Ohad Ben-Shahar.
In the drone area, where copters already accomplish a range of tasks from taking selfies to deliver packages, it is only imagination that limits what we can do with such devices. In this project we will develop a security drone to replace static surveillance camera system. This drone will possesses a certain degree of autonomy in paroling and securing a predefined property while streaming life video and reporting suspicious activities to the operator. For details please contact: Prof. Ohad Ben-Shahar.
A Scarecrow drone (or… the Pegion buster) (SE)
A practical problem in home maintenance, as well as in agricultural settings, is driving away harmful birds that either litter (e.g., pigeons at home) or damage yield (e.g., Pelecans or Gruses in the field). We wish to harness the power of drones, as autonomous flying agents equipped with proper sensing, to detect the presence of these creatures and fly closer to them in order to scare them away. In this project we will develop such a drone system with a certain degree of autonomy for monitoring a designated property (house or field) and protect it. For details please contact: Prof. Ohad Ben-Shahar.
Image extrapolator – predicting the unseen (CS)
What if we could predict reliably how an image (or any visual fragment) should look like beyond its borders? In this project we will implement both existing and novel methods, as well as mechanisms to evaluate these predictions. Most technique will be data-driven (using machine learning tools). For details please contact: Prof. Ohad Ben-Shahar.
Anamorphic synthesizer (CS)
If you ever been to Las Vegas, you may have visited the SLS hotel to see the stunning 3D show over the center bar. This form of anamorphosis is indeed particularly appealing and realistic for its dynamic nature, and is not terribly difficult to synthesize automatically from a dynamic 3D model of the scene. In this project we will implement such a system for any given display device and any given vantage point. For details please contact: Prof. Ohad Ben-Shahar.
Computational Art (CS,SE)
Computation is not the first thing that comes to mind in the context of artistic expression. But sometimes, art cannot be created without computation, if you will, as another manifestation of the emerging field of digital humanities. In this class of projects we will explore such combinations, possibly with the collaboration of the Department of the Arts at BGU. A first project will try to replicate Petros Vrellis’ “A New Way to Knit”, though not necessarily for circuar frame but for arbitrary convex one. Depending on the scope and scale of the project, a physical implementation using a robotic arm will be included also. Additional projects may include 3D printing as well. Fun is guaranteed!! For details please contact: Prof. Ohad Ben-Shahar.
Augmented Reality for architectural design (CS,SE)
Architects and interior designers design draw their plans as 2D sketches. Customers, however, are not able to visualize their house from these drawings and desired 3D simulations of their house. How wonderful could it be if this gap could be bridged directly from the 2D drawing using one’s smartphone. In this project we will implement a simple augmented reality system that observes simple 2D drawings of one floor houses and in real time augments the proper 3D structure over it. Additional features over the basic capacity will be considered along the project. For details please contact: Prof. Ohad Ben-Shahar.
From Shape of Drops to Contact lens that doesn’t irritate the eye (CS)
The shape of a drop bears important information on the surface tension of the drop and its wetting properties. This information can determine if our glasses will become foggy with droplets, or how to relate contact lenses to the teardrops of an individual person so that it will not irritate the user’s eyes. The basis for such studies requires a software that will recognize a drop image and differentiate between shapes of different drops. In this project we will work towards automatic extraction and description of the shape of drops that are suspended from a syringe, and, based on the shape, calculate the surface tension of the liquid. For details please contact: Prof. Ohad Ben-Shahar or Prof. Rafael Tadmor (Mechanical Engineering).
A high tech fish tank for the study of animal behavior (CS,SE)
Computational Vision could be a wonderful tool for the study of animal behavior. Indeed, instead of allocating human observers to monitor the animals and document their behavior, why not placing a camera and a computer to do so? In this project we will do exactly that to study unique behavioral patterns by gold fish and archer fish. In fact, we will develop a high tech fish tank that monitors the fish to report their psoe (location and direction) within the tank while controlling multiple feeders that reward the fish as soon as they reach certain locations in the tank or accomplish certain tasks. This project is part of a larger research project in collaboration with the Ronen Segev’s lab in the Life Sciences department and will result in the first-ever fully automatic fish tank that trains and observes fish behavior all by itself in order to answer scientific questions at the forefront of neuroscience. For details please contact: Prof. Ohad Ben-Shahar.
Deep learning for Shape from Shading (CS,SE)
Ill-posed inverse problems in vision (or other domains) are one-to-many problems where the I/O mapping is under-determined. In some very basic sense, the vision problem as a whole is one grand inverse problem. For decades now the computer vision community has been addressing such problems using regularized optimization – a fancy terms to say more constraints are needed to single our certain solutions over others. Could deep learning, the new king in town, do better? In this project we will study some literature and experiment with one of the most basic inverse problems vision, where the shape of objects is to be inferred from their images. For details please contact: Prof. Ohad Ben-Shahar.
Ongoing Projects (already assigned and running or completed)
Another drone-based project, suitable in particular to the BGU campus, we will attempt develop a system that find cars who park illegally around campus (or a given parking lot). Unlike BGU’s parking warden, who travels around the parking lot with his electric scooter, we will develop a drone system that does so automatically and registers illegally parking cars based on their windshield permit and the characterization of the parking lot. For details please contact: Prof. Ohad Ben-Shahar.
If Waze made ways social, Ize will do so for eyes. In this project we will develop a mobile application where our eyes are shared for the benefit of all. For details please contact: Prof. Ohad Ben-Shahar.
A computational generator of geometric visual illusions (CS,SE)
Optimal illusions are a fascinating phenomenon that captures the imagination and often provides insights into the function of our visual system. In this project we would like to develop an end-to-end system that generates topology-disturbing geometric optical illusions of the sort invented by Kokichi Sugihara and popularized in the 2016 best optical illusion contest and shown here. Such a system will allow users to specify the viewer and mirrors position (and we will even attempt to generalize the illusion to more than one mirror!) and what perceptual shapes are desired, and if those shapes prove produce the real 3D shape that one needs to generate in order to obtain the illusions. The system will also convert this shape to a proper representation (i.e., file format) that can be used with the 3D printers in our lab, so the illusions can be constructed in real life.
For details please contact: Prof. Ohad Ben-Shahar.