Particles explained using Gifs!!

Over the past few months, I have been reading, understanding and implementing a number of existing algorithms in Computer Vision domain. Implementing particles and particle based algorithms have really had me excited and almost on the edge of my seat. One may ask what makes particles so interesting?? Let me try to get the concept through.

Particles, just like most existing algorithms in computer science, are inspired by nature. Have you ever seen a beam of sunlight coming through a window and illuminate a bunch of floating particles (impossible in London though I have seen it before)? When you see these tiny particles, you notice that they are suspended in air and that it's very difficult to predict their motion unless you disturb the surrounding air. This simple concept is vital for many computer algorithms that model motion/dynamics of an object.

Particles, along with their randomness, can be simulated inside a computer program. The simplest of such algorithm is called Random Walk, where a particle is modelled with its current position/state alone and a random displacement/jump determines its next position in time. Here I have shown one Random Walk particle:

A Single Random Walk Particle

Particle Filtering - Survival of the fittest

I recently studied dynamic system models such as Kalman and Particle Filters.
For Kalman Filter I followed a Matlab demo that can be found here.

In this demo, the simple problem of tracking a ball is addressed using a Kalman Filter. The input sequence is of a ball, which is travelling at varying velocity and which is occluded in some frames by a box. I think this is a great example to demonstrate the power of dynamic system  models, especially the occluded frames can be used to test how good a dynamic model is. Here is the actual sequence:

As you can see the ball goes underneath the box and comes out of the other end. If our dynamic model is accurate it will be able to predict the state of the ball even when it is not visible, and should match the position when the ball comes out.

"Welcome to the Virtual World...may I take your username?"

Quick note: I wrote this a long time back, but never published - thought it wasn't good enough. This just occurred to me --> it's just a post - doesnt need to be perfect right?!? So posting this now - Please be sure to leave a comment with what you think!

Over the last few years, there have been some amazing advancements in gadgets - specifically the new imaging devices have emerged and a new horizon for virtual reality has been set. These devices have opened up a door for limitless future development possibilities. "Occulus Rift", the virtual reality head-mounted device that was received with overwhelming Kickstarter response, has been the pioneer in developing the key tech that can realise the virtual reality. The reason behind this huge success is an amazing idea which transfers all your senses into a digitally created world. Although this concept has been recently recognised, the idea has been around for decades.

Saying hello to the Internet of Things!

A while back I signed up for Microsoft Developer Program for Internet of Things ( #iot for more info ). As much as I love exploring new things this was extremely exciting thing for me.

I have always had the curiosity to know more and try to hack things my own way. Even as a kid I had an investigative mind which always tried to discover more about how everything works. You can imagine this curiosity by the fact that I got severe electric shock as a kid, when I tried to cut a live wire from "Clothes Iron". This curiosity grew more and more in me, to a point that I did an engineering degree (Yes! I was born with an engineer's mind). I have always been interested in hacking different devices to make something more useful out of it.

One Image hiding over eight thousand different stories...

Working with large datasets has its own pros and cons. Whatever the implementation or field might be, there is always a need for training a machine learning algorithm to recognize the pattern in that data. We often discuss this "Pattern" in many different instants and a big chunk of literature addresses this recognition problem. However it is often not considered important to get to know how this pattern looks like? why is it even called "Pattern" in the first place??

Interestingly the answer lies in the above image which shows a collection of 8000 different samples, arranged in columns. Here the first thing to notice is that there actually is a repeating pattern in the data. This is the exact pattern which we are trying to learn. It may not make sense when looking at it, however with correct label representation, each sample can be used to build a model which is able to identify each class with high accuracy.

Mind == Blown!

 So sometime back I saw this video presentation of a new and, what I like to call it, novel method for extracting 3D structures from a single image. Part of the reason why this blows my mind, is that this approach is well defined for a specific scenario and it utilizes the best of both human brain and computer's processing power.

We have a great sense of depth perception of objects. Our brains are well trained to construct an object's three dimensional model, by just looking at pictures. This, however, is a trivial and a highly challenging task for computer algorithms. On the other hand, computers are capable of computing and interpolating data at a much faster rate than humans, given that the task is simple and fairly straightforward.

Computer Vision is everywhere...

As most of the android developers, I am a big fan of google nexus tablets and smartphones. Have been using a google nexus 4 for a while now and I am impressed by all kinds of cool stuff you can do with it. A number of cool applications are based on different computer vision techniques. In this post I will be discussing these applications.

 

 

To list just a few obvious ones, the android based smartphones have face recognition based unlocking, camera app which can pick up faces, creating panoramas, editing photos and using readings from a number of inertial sensors to stitch multiple picture into one 3D picture called Photo Sphere.

 

OUT-A-TIME: What is the fourth dimension?

I have been doing my research using three dimensional datasets acquired from both real and synthetic methods. During my past research I utilized Microsoft Kinect to acquire real-world objects in their three dimensional space. On the contrary I have also used computer graphics to generate such three dimensional datasets. Some other projects I have worked on have also revolved around concepts which were vaguely related to different multi-dimensions.

Working with these multi-dimensional datasets, I have always been interested in finding out how these multi-dimensions would exist in reality (if they ever did). Here I was more interested in the question about physical space we live in. Annoyingly this has always confused me. I simple could not comprehend more than three dimensions.

For those of you who are familiar with the picture below, this post is going to be as interesting for you to read as it was for me to write.

The Universe is in us!

I have been away from this blog for a while, and there are a number of reasons for that. Mostly I have been really really lazy with lots of work and sleep. The good news is that I am back and I have quite a few things to post about.

While reading this, you might be wondering what this post is about? Well its about surprising similarities between two totally different worlds. The first one involves the microscopic world of DNA. The data I used is specifically cancer mutated DNA I was provided when I went to a GameJam for Cancer Research UK. One of the problems we tried to address in this gamejam was to identify the regions in DNA with cancer mutations. Being a Computer Vision Engineer, I have been really interested on representing the data in a visual way. While I might not have succeeded in creating something useful, however what I found was quite interesting.

Game hackathon for Cancer Research UK

Over the weekend I was at the google campus london for the hackathon for Cancer Research UK. The objective of this hackathon was to convert dna data into an interactive and social game to help accelerate the cancer research. The data provided by Cancer Research UK had different mutations in dna, which could be identified by sudden shift in the data points. Approximately 40 developers and gamer spent 48 hours to design different games that utilized this data, had the social gaming experience and above all provided some feedback for easy identification of the dna mutations resulting in Cancer.

The outcome was a number of games with different diverse ideas, each one focusing on one thing, to analyse the data using human eye. More details on this event coming soon, as we are all waiting to hear about it from Cancer Research UK.

Report on this event can be found here: bit.ly/WsTB1B
City University Press Release on this event: http://tinyurl.com/cmxdbyc