Bag of Visual Words Model

Bag of Visual Words Model Abstract Automatic interpretation of Remote sensing images is a very important task in several practical fields. There are several approaches to accomplish this task, one of the most powerful and effective approach is the use of local features and machine learning techniques to detect objects and classify it. In such an approach, first, the image is scanned for local features and coded in a mathematically manipulatable form, then these local features are injected to a classifier to get the class of the object which contains these local features. In this thesis, bag of visual words model for detecting and recognizing of objects in high resolution satellite images is constructed and tested using blob local features. Scale Invariant Feature Transform (SIFT) and Speedup Robust Features (SURF) algorithms are used as blob local feature detector and descriptor. The extracted features are coded mathematically with Bag of Visual Words algorithm in order to represent an image by the histograms of visua l words. Dimension reduction technique is used to eliminate non-relevant and non-distinctive data using Principle Component Analysis (PCA). Finally, a single class Support Vector Machine (SVM) classifier is used to classify the object image as a positive or negative match. We extend the typical use of BOVW by using an object proposals technique to extract regions that will be classified by the SVM depends on keypoints location clustering instead of sliding window approach. Besides enhance the resolution independency by using geospatial info extracted from the remote sensing images meta-data to extract real dimensions of objects during training and detection. The whole approach will be tested practically in the experiment work to prove that this approach is capable to detecting a number of geo-spatial objects, such as airplane, airports and cars. Introduction The remote sensing, images has been developed in quantity and quality and its applications. The image itself is not useful without analysis. The analysis is to generate information from the image.ÂÂ   One of the image analysis tasks is the detection of objects from the images, either man-made objects or natural objects. The automation of this task is very useful in real world applications, but it is very challenging. This can be one of the computer vision field problems. The methods that, use local features in object, recognition from visual data is very successful in recent researches. The benefits of using local features is immunity, to occlusion, and clutter, and with greatest significantly, no pre-step of segmentation, is required before local feature extraction. The accessibility of diverse feature extraction and descriptors algorithms lets local feature methods efficient. Furthermore, the large number of features, generated from images of objects is crucial advantage, of l ocal features. While the benefits of local features are useful, a feature has to cover some factors; like invariance to scaling, rotation, illumination, viewing direction slight change, noise and cluttering. Motivation The revolutionary technology used in new generation satellite systems is driving the development of new large scale data handling approaches in remote sensing related applications. Furthermore, the large image archives captured over the previous missions are now being used to produce innovative global products. In particular, the development of large-scale analytics tools to efficiently extract information and apply the achieved results towards answering scientific questions represents a big challenge for the research community working in the Remote Sensing field. One of the most useful analytic tools in remote sensing images is the object detection and recognition, either the man-made objects or natural ones as shown in Figure ‎1‑1 Figure ‎1‑1 Object detection as a Remote sensing image interpretation analysis There are a lot of challenges faced by the researchers like, but not limited to, enhancing the efficiency to process large data, developing the suitable techniques to detect and recognize various object types and develop tools and platforms needed to store, analyze, interpret and represent data and results. These challenges united experts of data science, algorithm development and computer science, as well as environmental experts and geoscientists, to present state-of-the-art algorithms, tools, and applications for processing and exploitation of a huge amount of remotely sensed data. The scope of these researches can be generalized as following: Studies describing advanced approaches to process large volume of multi-temporal optical, SAR (Synthetic Aperture Radar) and radiometric data. Studies discussing innovative techniques, and associated data processing methods for very large-scale data exploitation. Critical analyses of existing and innovative tools, methods and techniques for large-scale analytics to extract and represent information Results of case studies executed at different large spatial and temporal scales, also by using GRID and/or Cloud Computing platforms. Results of on-going national/international initiatives and solutions for managing, processing, and disseminating huge archives of Remote Sensing data and relevant results. Problem Statement This thesis addresses the problem of geospatial object detection and recognition from high resolution satellite images. The problem we are trying to solve is to decide if a given aerial, or satellite image, contains one or more objects, belonging to the class of interest, and locate the position, of each predicted object, in the image. The expression object stated in this thesis is any type of object may appear in the remote sensing images, including man-made objects which have sharp edges and are distinct from the background, for example a building, a ship, a vehicle. Our solution must be consider the challenges and difficulties of object detection in optical remote sensing images like visual appearance variations which caused by occlusion, viewpoint variation, clutter, illumination variation, shadow variation, etc. A general statement of the problem can be formulated as follows: Given a remote sensing image contains different objects, it is required to decide if one or more occurrences of a specific object class is existing in this image, and if so, detect locations of these objects, this needs to be successful in case of variation of viewpoint, occlusion, background clutter Objectives Model a methodology to solve the problem stated above that can features the following: Acquire training data of unlimited object classes. Read high resolution remote sensing images and able to analyze its data. Detect occurrences of trained object classes in the remote sensing images Demonstrate results as a geo-referenced data type. In this thesis, we will demonstrate a model to achieve these objectives, and assess its results compared to other state-of-the-art models presented in the recent researches. Thesis Layout The thesis is composed of five chapters, the first chapter presenting an introduction stating the motivation, problem definition and objectives, second chapter is discussing the literature survey about the problem and researches in the field, third chapter presenting a detailed explanation of the methodology proposed to solve the problem. Fourth chapter contains the experimental results of the model. Fifth chapter discusses and concludes the methodology represented in this thesis, then a few points is suggested as a future work.

Case Study Analysis Essay

The case study I chose to evaluate was Oak Brook Medical Systems, Inc. The manager, Jackie, is known as a â€Å"no nonsense† kind of manager who is credited with large increases in business accounts resulting in a $40 million dollar addition to the corporate bottom line. She is a valuable corporate asset but has considerable communication issues with staff members. This is a so called â€Å"armchair† case study that is based on the fictional documentation produced by O’Rourke in case 10-1 (2010) Business Problem Part of the problem faced by Oak Brook Medical Systems is Jackie. She is difficult to communicate with and on occasion, makes other staff members feel their contribution to the welfare of the company is less important than her own. Workers feel unappreciated and Jackie is sometimes short tempered and condescending toward her coworkers and subordinates. Jackie believes the issue to be no more than a hurdle that has been faced by many who went before her. She believes that the issues with her subordinates are no different than those faced by every manager or superior, not suspecting that the issue may actually lie with her. From Jackie’s perspective, the staff problems are due in part to her race. Jackie is of African American descent and, as such, is perhaps a little more observant of people’s attitude toward her than other employees would be. She is beginning to believe that the company may prefer to have a non-black in the position she currently holds; and would rather she not advance any further with the company. Jackie has known nothing but success in her life and is having difficulty recognizing hurdles to advancement because she has not faced failure in her past. She cannot understand the reason she is not progressing more within the company and does not consider her communication issues with fellow staff members as anything more than a nuisance to her advancement. The business problem for Oak Brooke Medical Systems is how to improve communication between staff members and prevent Jackie from demeaning her subordinates by her very direct approach to management. Critical Issues The issues faced by Oak Brooke Medical Systems, Inc., are related to communication and human resources. If staff feels they have no support in dealing with an overly aggressive manager, the company will lose vital talent and the creativity of the remaining members may be inadvertently subdued by fear or perceived bullying. The loss of current staff members could pose a long-term problem for the company as attracting and cultivating talented team members is costly and time consuming. If Jackie can eliminate one or more of the other members of the team by her aggressive managerial stance, she may ultimately cost the company more than she generates in revenue. Jackie is also a talented team member; but tends to want to play alone and seldom seeks the approval of other staff members. She has a direct approach to management and can steam-roller over others to reach her goal. She is African American and this will ultimately become an issue should the company decide to discipline her for unacceptable behavior. In the short term, Jackie believes her color is hindering her advancement within the company. Possible Solutions Jackie is exceptional at producing profits for the company. If Oak Brooke was willing to invest further in Jackie and provide some cultural training and sensitivity classes she may benefit. If Jackie can make other team members feel their contribution is important and indeed welcome, she may be able to generate a wave of support rather than create an unpalatable hostility in the workplace (Vlachoutsicos, 2011). Staff members may also benefit from cultural training and perhaps they would be more accepting of Jackie’s stance with regard to upward mobility in the corporation. IF team members understood the perceived hurdles Jackie faced in her work, they may be able to accommodate slightly more than they are currently able to. Meetings to openly discuss issues that staff have with Jackie and vice versa, may be all that it takes to settle the workplace down to something more easily managed. According to O’Rourke (2010), we all judge people by a standard to which we are accustomed and that standard is set by our experiences, values, education, and beliefs. Being able to recognize differences in the experiences of others is a big step toward building the bridges to successful communication. Racial bias is a two-way street and it should be made clear to all involved in the resolution that they must each understand the issue from the perspective of the other party or negotiations will be futile. References O’Rourke, J. S. (2010). Management communication: A case-analysis approach (4 ed.). Upper Saddle River, NJ: Pearson Education, Inc. Vlachoutsicos, C. A. (2011). How to Cultivate Engaged Employees. Harvard Business Review, 89(9), 123-126.

April Themes, Holiday Activities, and Events

The Issue Of Immigration Is Become A Major Debate For...

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