# Image Classification Using Fisher Vectors

This is a continuation of my previous blog post on image classification and the bag of words (BoW) model. If you already know how BoW works, then you will feel right at home. If you need a refresher, you can read the blog post here. In our previous post, we discussed how BoW works, and how we construct the codebook. An interesting thing to note is that we don’t consider how things are ordered as such. A given image is treated as a combination of codewords regardless of where they are located with respect to each other. If we want to improve the performance of BoW, we can definitely increase the size of the vocabulary. If we have more codewords, we can describe a given image better. But what if we don’t want to do that? Is there a more efficient method that can be used?   Continue reading “Image Classification Using Fisher Vectors”

# Image Classification Using Bag-Of-Words Model

Image classification is one of the classical problems in computer vision. Basically, the goal is to determine whether or not the given image contains a particular thing like an object or a person. Humans tend to classify images effortlessly, but machines seem to have a hard time doing this. Computer Vision has achieved some success in the case of specific problems, like detecting faces in an image. But it has still not satisfactorily solved the problem for the general case where we have random objects in different positions and orientations. Bag-of-words (BoW) model is one of the most popular approaches in this field, and many modern approaches are based on top of this. So what exactly is it?   Continue reading “Image Classification Using Bag-Of-Words Model”

# What Is Gamma Correction?

Gamma correction is an integral part of all the digital imaging systems, but a lot of people don’t know about it! It is an essential part of all the imaging devices like cameras, camcorders, monitors, video players, etc. It basically defines the relationship between a pixel’s numerical value and its actual luminance. Now wait a minute, why would they be different? Isn’t a pixel’s numerical value supposed to be exactly the same as its luminance? Well, not really! Without gamma, shades captured by digital cameras wouldn’t appear as they did to our eyes. If we fully understand how gamma works, we can improve our exposure technique, along with making the most of image editing. So what is it all about? Why do we need gamma correction at all?   Continue reading “What Is Gamma Correction?”

# Recognizing Shapes Using Point Distribution Models

In the field of computer vision, we often come across situations where we need to recognize the shapes of different objects. Not only that, we also need our machines to understand the shapes so that we can identify them even if we encounter them in different forms. Humans are really good at these things. We somehow make a mental note about these shapes and create a mapping in our brain. But if somebody asks you to write a formula or a function to identify it, we cannot come up with a precise set of rules. In fact, the whole field of computer vision is based on chasing this hold grail. In this blog post, we will discuss a particular model which is used to identify different shapes.   Continue reading “Recognizing Shapes Using Point Distribution Models”

# What Is Random Walk?

Consider the following situation. We have a drunkard who is clinging to a lamppost, and now he decides to start walking. He is in the middle of the street and the road runs from east to west. In his inebriated state, he is as likely to take a step towards the east as he is towards the west. It just means that there is a 50% chance that he will go in either direction. From each new position, he is again as likely to go east or west. Each of his steps are of the same length but in random direction. After having taken ‘n’ number of steps, he is to be found standing at some position on the street. This is what a random walk is. We can plot the position against the number of steps taken for any particular random walk. Now the question is, can we model his movement so that we can predict where he will be after taking ‘n’ steps?   Continue reading “What Is Random Walk?”

# Purkinje Effect

Ever wondered why the colors seem to change at night? For example, if you look at an air painting, you can see how the colors of objects look radically different in very low light just before dawn or dusk. Consider a red rose, for instance. We know that the flower’s petals are bright red against the green of the leaves in daylight. But, take a look at dusk and you will see that suddenly the contrast is reversed, with the red flower petals now appearing dark red or dark warm gray, and the leaves appearing relatively bright. Bright red doesn’t remain bright red anymore, and green doesn’t remain green either. They all become a bit monochromatic and it becomes difficult to separate them. Why does this happen?   Continue reading “Purkinje Effect”

# Asymmetric Dominance Effect

Let’s consider a situation. There is a company with two products, A and B. Both these products have their own merits and demerits. Product A has relatively less features, but it’s price is low. Product B, on the other hand, has more features but it’s more expensive. Consumers tend to pick both these products depending on their needs. Now the company introduces a third product, C. The asymmetric dominance theory says that you can affect the consumer behavior using this third product. You can make the consumers shift towards product A or product B by designing product C in different ways. Now how is that possible? How can we change consumer preference between A and B without even modifying these products?   Continue reading “Asymmetric Dominance Effect”

# Can Machines Be Truly Independent?

In my previous blog post, we discussed about how we can measure a computer’s intelligence. When we talk about machine intelligence, what exactly are we talking about? Are we just talking about machines mimicking the human ways and mannerisms in the best possible way? No matter what the machines do, they are still following a predefined sequence of steps or an algorithm that dictates the sequence of steps. The field of artificial intelligence has been trying for a long time to put actual intelligence into a machine, but we are still far from it. The question then would be, can machines be truly independent?   Continue reading “Can Machines Be Truly Independent?”

# Can We Measure A Computer’s Intelligence?

People talk about artificial intelligence all the time. Artificial intelligence is the branch of study which deals with putting intelligence into the machines so that they can do things by themselves. But how do we know if they are getting intelligent? For us humans, we have designed various kinds of IQ tests to measure our intelligence. Is there anything for machines as well? I am not talking about the robustness of an algorithm or the accuracy with which a computer can finish a certain task, I am talking about the actual intelligence. Is it possible to measure it?   Continue reading “Can We Measure A Computer’s Intelligence?”

# What Does Backpropagation Mean?

People started working on artificial intelligence back in the late ’60s. After they came up with the concept of perceptron, this field looked very promising. But as the years passed by, no significant development took place even after making several attempts from multiple directions! As people were beginning to lose hope, backpropagation came into picture and breathed new life into this field. Backpropagation was the result of pioneering work by mathematicians and computer scientists, which eventually led to a successful revival of artificial intelligence! So what exactly is backpropagation? How is it used in real life?   Continue reading “What Does Backpropagation Mean?”