This paper presents a method that expresses the fringe pattern as an exponential function and a mathematical model for gamma-independent phase computation. The method was compared to: (i) conventional phase measurement without nonlinearity correction, and (ii) conventional gamma correction by pattern pre-distortion based on an input-to-projector camera-output look-up table. The pre-distorted and exponential methods achieved large reduction in error compared to conventional computation with no gamma correction. The advantage of the exponential method is that no system gamma nonlinearity calibration procedure or information is required. This reduces optical system setup before measurement and permits easier use of off-the-shelf projectors.

Data is today's most powerful tool; valuable facts and information can be determined by analyzing them using appropriate techniques and algorithms. Also, the rapid increase in access to Internet technology to a large mass of people worldwide has increased the importance of analyzing data generated on the web much more than before. The preceding discussion of this research is sales forecasting in marketing, which is very important in this topic. Marketing is a tool through which people's standard of living is developed, which is done before and after the sale. This research presents a model based on a dynamic analysis system for forecasting marketing sales based on the AGA-LSTM neural network model. It is challenging to recognize emotions in natural language, even for humans, and automatic recognition makes it more complicated. This research presents a hybrid deep-learning model for accurate sentiment prediction in real-time multimodal data. In the proposed method, the work process is such that after extracting emotional data from social networks, they are pre-processed and prepared for pattern discovery. The data is evaluated in the adaptive genetic algorithm, and the pattern is discovered in the designed neural network, and this pattern is discovered after discovery. The cornerstone of sales policies is improved. The adaptive genetic algorithm was used to optimize the parameters of the LSTM model, and the model can predict the types of goods and the total volume of online retail sales. In the simulation of the proposed method, in 3000 rounds of training, an accuracy of 76 has been achieved, which is an improvement of 11% compared to the primary method.

ABSTRACT:3D reconstruction has been already one of the most interesting research areas among photogrammetry and computer vision researchers. This thesis aims to evaluate digital fringe projection method in reconstruction of small objects with complicated shape. Digital fringe projection method is a novel method in structured light technique which integrates interferometric and triangulation methods. In this method, a digital projector projects a series of sinusoidal fringe patterns onto the object surface. Then, a camera from a different point of view captures images of patterns that are deformed due to object's surface topography. Afterward, the captured images will be processed and the depth related phase would be calculated. Due to using arctangent function in the process of phase extraction, the computed phase ranges from -pi to +pi, so a phase unwrapping step is necessary. Finally, the unwrapped phase map would be converted to depth map with some mathematical models. This method has many advantages like high speed, high accuracy, low cost hardware, high resolution (each pixel will have a depth at end), and simple computations. This paper aims to evaluate different parameters which affect the accuracy of the final results. For this purpose, some test were designed and implemented. These tests assess the number of phase shifts, spatial frequency of the fringe pattern, light condition, noise level of images, and the color and material of target objects on the quality of resulted phase map. The evaluation results demonstrate that digital fringe projection method is capable of obtaining depth map of complicated object with high accuracy. The contrast test results showed that this method is able to work under different ambient light condition; although at places with high light condition will not work properly. The results of implementation on different objects with various materials, color and shapes demonstrate the high capability of this method of 3D reconstruction.