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Full-Text Articles in Engineering
Extracting Depth Information From Stereo Vision System, Using A Correlation And A Feature Based Methods, Mahmoud Abdelhamid
Extracting Depth Information From Stereo Vision System, Using A Correlation And A Feature Based Methods, Mahmoud Abdelhamid
Mahmoud M Abdelhamid
This thesis presents a new method to extract depth information from stereo-vision acquisitions using a feature and a correlation based approaches. The main implementation of the proposed method is in the area of Autonomous Pick & Place, using a robotic manipulator. Current vision-guided robotics are still based on a priori training and teaching steps, and still suffer from long response time. The study uses a stereo triangulation setup where two Charged Coupled Devices CCDs are arranged to acquire the scene from two different perspectives. The study discusses the details of two methods to calculate the depth; firstly a correlation matching …
Model-Free Method Of Reinforcement Learning For Visual Tasks, Jeff S. Soldate, Jonghoon Jin, Eugenio Culurciello
Model-Free Method Of Reinforcement Learning For Visual Tasks, Jeff S. Soldate, Jonghoon Jin, Eugenio Culurciello
The Summer Undergraduate Research Fellowship (SURF) Symposium
There has been success in recent years for neural networks in applications requiring high level intelligence such as categorization and assessment. In this work, we present a neural network model to learn control policies using reinforcement learning. It takes a raw pixel representation of the current state and outputs an approximation of a Q value function made with a neural network that represents the expected reward for each possible state-action pair. The action is chosen an \epsilon-greedy policy, choosing the highest expected reward with a small chance of random action. We used gradient descent to update the weights and biases …
Ear Contour Detection And Modeling Using Statistical Shape Models, Satish Ravindran
Ear Contour Detection And Modeling Using Statistical Shape Models, Satish Ravindran
All Theses
Ear detection is an actively growing area of research because of its applications in human head tracking and biometric recognition. In head tracking, it is used to augment face detectors and to perform pose estimation. In biometric systems, it is used both as an independent modality and in multi-modal biometric recognition. The ear shape is the preferred feature used to perform detection because of its unique structure in both 2D color images and 3D range images. Ear shape models have also been used in literature to perform ear detection, but at a cost of a loss in information about the …