Engineering Commons^™

On Action Quality Assessment, Paritosh Parmar

UNLV Theses, Dissertations, Professional Papers, and Capstones

In this dissertation, we tackle the task of quantifying the quality of actions, i.e., how well an

action was performed using computer vision. Existing methods used human body pose-based features to express the quality contained in an action sample. Human body pose estimation in actions such as sports actions, like diving and gymnastic vault, is particularly challenging, since the athletes undergo convoluted transformations while performing their routines. Moreover, pose-based features do not take into account visual cues such as water splash in diving. Visual cues are taken into account by human judges. In our first work, we show that using …

Foreground Removal In A Multi-Camera System, Daniel T. Mortensen

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Traditionally, whiteboards have been used to brainstorm, teach, and convey ideas with others. However distributing whiteboard content remotely can be challenging. To solve this problem, A multi-camera system was developed which can be scaled to broadcast an arbitrarily large writing surface while removing objects not related to the whiteboard content. Related research has been performed previously to combine multiple images together, identify and remove unrelated objects, also referred to as foreground, in a single image and correct for warping differences in camera frames. However, this is the first time anyone has attempted to solve this problem using a multi-camera system. …

Machine Learning And Image Processing For Noise Removal And Robust Edge Detection In The Presence Of Mixed Noise, Mehdi Mafi

FIU Electronic Theses and Dissertations

The central goal of this dissertation is to design and model a smoothing filter based on the random single and mixed noise distribution that would attenuate the effect of noise while preserving edge details. Only then could robust, integrated and resilient edge detection methods be deployed to overcome the ubiquitous presence of random noise in images. Random noise effects are modeled as those that could emanate from impulse noise, Gaussian noise and speckle noise.

In the first step, evaluation of methods is performed based on an exhaustive review on the different types of denoising methods which focus on impulse noise, …

Height Measurement Of Basil Crops For Smart Irrigation Applications In Greenhouses Using Commercial Sensors, Leila Bahman

Electronic Thesis and Dissertation Repository

Plant height is a key phenotypic attribute that directly represents how well a plant grows. It can also be a useful parameter in computing other important features such as yield and biomass. As the number of greenhouses increase, the traditional method of measuring plant height requires more time and labor, which increases demand for developing a reliable and affordable method to perform automated height measurements of plants. This research is aimed to develop a solution to automatically measure plant height in greenhouses using low cost sensors and computer vision techniques. For this purpose, the performance of various depth sensing technologies …

System And Method For Radio Tomographic Image Formation, Richard K. Martin

AFIT Patents

A system and method for generating radio tomographic images is provided. A plurality of transceivers positioned around a region to be imaged is divided into a plurality of pixels. A control apparatus is configured to cause each of the plurality of transceivers in turn to send a signal to each of the other transceivers. The control apparatus is further configured to determine an attenuation in the received signals, generate weighing, derivative, and attenuation matrices from the signals, group the pixels into a plurality of provinces, select each province in turn and solve for a change in attenuation in each of …

Erratum: "Imaging The Three‐Dimensional Orientation And Rotational Mobility Of Fluorescent Emitters Using The Tri‐Spot Point Spread Function", Oumeng Zhang, Jin Lu, Tianben Ding, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

In the original paper, a calibration error exists in the image-formation model used to analyze experimental images taken by our microscope, causing a bias in the orientation measurements in Figs. 2 and 3. The updated measurements are shown in Fig. E1. We have also updated the supplementary material for the original article to discuss the revised PSF model and estimation algorithms (supplementary material 2) and show the revised model and measurements (Figs. S1, S3, S7, S8, and S10–S13).

Segmentation And Registration Based Automatic Cancer Proton Treatment Analysis, Yang Zhang

Open Access Theses & Dissertations

Due to its low side effects, proton therapy is rapidly developing around the world. However, the time and labor it takes to deliver the treatment have prevented widespread use in the clinic setting. For this reason, an automatic proton treatment analysis system is needed to improve efficiency during the treatment process.

The challenge lies in improving the accuracy and speed of the current proton treatment analysis system. The Range shifter correction factor is considered the same value under any given condition in our treatment system. This approximate algorithm limits the accuracy of the proton treatment analysis system. In addition, medical …

Multi-Pig Part Detection And Association With A Fully-Convolutional Network, Eric T. Psota, Mateusz Mittek, Lance C. Pérez, Ty Schmidt, Benny Mote

Department of Electrical and Computer Engineering: Faculty Publications

Computer vision systems have the potential to provide automated, non-invasive monitoring of livestock animals, however, the lack of public datasets with well-defined targets and evaluation metrics presents a significant challenge for researchers. Consequently, existing solutions often focus on achieving task-specific objectives using relatively small, private datasets. This work introduces a new dataset and method for instance-level detection of multiple pigs in group-housed environments. The method uses a single fully-convolutional neural network to detect the location and orientation of each animal, where both body part locations and pairwise associations are represented in the image space. Accompanying this method is a new …

A Novel Method Of Near-Miss Event Detection With Software Defined Radar In Improving Railyard Safety, Subharthi Banerjee, Jose Santos, Michael Hempel, Pejman Ghasemzadeh, Hamid Sharif

Department of Electrical and Computer Engineering: Faculty Publications

Railyards are one of the most challenging and complex workplace environments in any industry. Railyard workers are constantly surrounded by dangerous moving objects, in a noisy environment where distractions can easily result in accidents or casualties. Throughout the years, yards have been contributing 20–30% of the total accidents that happen in railroads. Monitoring the railyard workspace to keep personnel safe from falls, slips, being struck by large object, etc. and preventing fatal accidents can be particularly challenging due to the sheer number of factors involved, such as the need to protect a large geographical space, the inherent dynamicity of the …

Segmentation And Registration Based Automatic Cancer Proton Treatment Analysis, Yang Zhang

Open Access Theses & Dissertations

Due to its low side effects, proton therapy is rapidly developing around the world. However, the time and labor it takes to deliver the treatment have prevented widespread use in the clinic setting. For this reason, an automatic proton treatment analysis system is needed to improve efficiency during the treatment process.

The challenge lies in improving the accuracy and speed of the current proton treatment analysis system. The Range shifter correction factor is considered the same value under any given condition in our treatment system. This approximate algorithm limits the accuracy of the proton treatment analysis system. In addition, medical …

On Board Georeferencing Using Fpga-Based Optimized Second Order Polynomial Equation, Dequan Liu, Guoqing Zhou, Jingjin Huang, Rongting Zhang, Lei Shu, Xiang Zhou, Chun Sheng Xin

Electrical & Computer Engineering Faculty Publications

For real-time monitoring of natural disasters, such as fire, volcano, flood, landslide, and coastal inundation, highly-accurate georeferenced remotely sensed imagery is needed. Georeferenced imagery can be fused with geographic spatial data sets to provide geographic coordinates and positing for regions of interest. This paper proposes an on-board georeferencing method for remotely sensed imagery, which contains five modules: input data, coordinate transformation, bilinear interpolation, and output data. The experimental results demonstrate multiple benefits of the proposed method: (1) the computation speed using the proposed algorithm is 8 times faster than that using PC computer; (2) the resources of the field programmable …

Accurate And Compact Stochastic Computations By Exploiting Correlation, Hamdan Abdellatef, Mohamed Khalil Hani, Nasir Shaikh-Husin

Turkish Journal of Electrical Engineering and Computer Sciences

Recent studies have shown, contrary to what was previously believed, that by exploiting correlation in stochastic computing (SC) designs, more accurate SC circuits with low area cost can be realized. However, if these basic SC circuits or blocks are cascaded in series to form a large complex system, correlation between stochastic numbers (SNs) from one block to the next would be lost; thus, inaccuracies are introduced. In this study, we propose correlating circuits to be used in building complex correlated SC systems. One of the circuits is the correlator that restores lost correlations between two SNs due to previous processing. …

A Multiseed-Based Svm Classification Technique For Training Sample Reduction, Imran Sharif, Debasis Chaudhuri

Turkish Journal of Electrical Engineering and Computer Sciences

A support vector machine (SVM) is not a popular method for a very large dataset classification because the training and testing time for such data are computationally expensive. Many researchers try to reduce the training time of SVMs by applying sample reduction methods. Many methods reduced the training samples by using a clustering technique. To reduce its high computational complexity, several data reduction methods were proposed in previous studies. However, such methods are not effective to extract informative patterns. This paper demonstrates a new supervised classification method, multiseed-based SVM (MSB-SVM), which is particularly intended to deal with very large datasets …

Elimination Of Useless Images From Raw Camera-Trap Data, Ulaş Tekeli̇, Yalin Baştanlar

Turkish Journal of Electrical Engineering and Computer Sciences

Camera-traps are motion triggered cameras that are used to observe animals in nature. The number of images collected from camera-traps has increased significantly with the widening use of camera-traps thanks to advances in digital technology. A great workload is required for wild-life researchers to group and label these images. We propose a system to decrease the amount of time spent by the researchers by eliminating useless images from raw camera-trap data. These images are too bright, too dark, blurred, or they contain no animals. To eliminate bright, dark, and blurred images we employ techniques based on image histograms and fast …