|M.Sc Student||Ofir Avni|
|Subject||Biologically Motivated Modeling and Imitating the|
Chameleon's Vision System
|Department||Department of Computer Science||Supervisor||Full Professor Rivlin Ehud|
|Full Thesis text|
This thesis takes the biologically motivated approach with regard to the visual system of the chameleon. The chameleon has a unique visual system, in which the two eyes scan independently the environment. In the first part of this work, a complex and innovative computer vision system, which uses cameras and mirrors, is designed and implemented in order to track the direction of the eyes of chameleons. In this part the problem of pose estimation with multiple cameras and mirrors is formulated and solved. The problem is formulated as a minimization problem of the three-dimensional geometric errors given the location of features found in the image and their three-dimensional model. The direction of the eyes is found by founding the eyelid in the image, and based on a geometric model of the eye. Preliminary results from this part, which includes biological experiments, indicates that chameleons scan the environment using a ``negative correlation'' strategy. That is, when one eye scans forward, the other, with high probability, scans backwards.
In the second part, a robotic system based on the chameleon visual system is constructed. Based on the observation from the first part, a new method for visual scanning with a set of independent pan-tilt cameras is presented. The method combines information about the environment and a model for the motion of the target to perform optimal scanning based on stochastic dynamic programming. For the implementation, a model-based control strategy is developed that performs target tracking. A switching control, combining smooth pursuit and saccades, is proposed. Robust and Minimum-time Model Predictive Control (MPC) theory is used for the design of the control law.
Finally, simulative and experimental validation of the approach is presented. The scanning algorithm was simulated in matlab, and the resulting scanning pattern has a remarkable resemblance to the scanning behavior of chameleons. The target tracking method was implemented in a real-time system of two cameras mounted on top of pan-tilt heads. Experimental results of tracking a target are presented.