Estimating the Focus of Expansion (FoE)

One of the most intriguing things about Optical Flow is the calculation of Focus of Expansion or FoE. FoE is the point where all flow vectors converge when  a camera moves in a forward direction. It often indicates the direction where a camera is heading or aimed at, and is also regarded as the same point where flow vectors diverge from when the camera moves backwards. FoE plays a key role in most computer vision applications, including self-driving cars, guided missiles, obstacle detection and in robotics. To succeed in its applications, FoE should be calculated in real-time consistently at a fairly accurate level. The following is a demonstration of my algorithm for this, where I estimate the FoE using a probabilistic approach. This calculates the FoE for a single camera that has an inconsistent motion model.

The red circle signifies the FoE in question below.

Here I first obtain a set of sparse flow vectors as described in here. The flow vectors are obtained at frame rate using the Lucas Kannade method and when the number of flow vectors fall below a minimum threshold, flow vectors are re-calculated. Then the algorithm seeks the linear functions for those flow vectors (normalized) and then finds the intersection points for those linear functions. In the ideal case, these intersection points must coincide with each other as it theoretically represents the FoE, but due to the error, they don’t. Therefore we need to filter out the error. To do this, intersection points are arranged into a histogram and then the maximum bin will be taken out. Intersection points that fit inside the maximum bin are further filtered out through a Discrete Kalman Filter in order to estimate (or predict) the most likely intersection point (i.e. FoE).

 

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How to think like Steve Jobs..

41eiLo9-t-L._SX311_BO1,204,203,200_I love books that add value to our lives and provide us with lot of inspiration. This particular book titled
How to think like Steve Jobs” happened to grab my attention out of nowhere when I was browsing through the personal library of my wife’s father. It’s true that there are numerous books written by many, under the label of Steve Jobs, and I believe they all share the wisdom of Steve Jobs in overall, no matter how different their stories are.

In the course of reading this book “How to think like Steve Jobs“, I was able to harness an array of material on this man, once known as the hardest-working man in Silicone Valley, and how he transformed the computer and music industries. He was known to lead Apple from its humble beginnings, starting it off in his parents’ garage to the global empire it is today. So the big question for everybody, (especially after his death) was How did he do it? In this book, the author tries to answer this question by drawing out key elements on Job’s life and work, and about his vision towards technology. In fact, the book suggests that everything Jobs produced (Mac, iPod, iPhone, iPad) has the personality, charisma and his style built-in to them. So it’ll be worthy to study his life rather than his products so we could add some value to our lives and view the world from the eyes of a visionary.

In this post I intend highlight some of the key elements from this book, that took my attention, as in below. Continue reading “How to think like Steve Jobs..”

Abdul Kalam: A Valuable Role Model

Wings-Of-FireDr. Abdul Kalam is perhaps India’s most admired technocrat who once led the country’s space rocketry and missile programme into monumental heights. I recently came across his autobiography ‘Wings of Fire‘ which is a fascinating account of his life and work and a story full of inspiration. In spite of being brought up in a rural village and a son of an ordinary boat-owner, his ceaseless courage was ultimately well paid off at the end by becoming the most distinguished person in India – the country’s 11th President. But yet, what captivated me most is his humble and unassuming nature and the way he maintained it throughout his life. Following are some of the useful traits that I could pick up from his deeply passionate personal story, which I believe will enlighten our lives too.
Continue reading “Abdul Kalam: A Valuable Role Model”

AR and its Role in Marking Space

It is perhaps surprising to realize that only two things in this world have troubled man’s ingenuity for centuries, i.e. space and time. These two are absolute benchmarks, often used when making a reference to a physcial object in space or when describing a past incident, though it is hard to understand why do we always attribute our actions or events in relation to space and time. For instance, a special event (a birthday perhaps) can be expressed in relation to time by marking that occurence on a calendar either digitally or manually. We are capable of doing this since ’time’ as we know of, is one dimensional. It is somewhat puzzling at this point, should we deal with space in the same manner, because space is three dimensional and it provides freedom for travelling in multiple directions, as opposed to the single dimensional nature of time. These implications led our curiosity to focus on one implicit feature, yet something strange about space – ”How can we mark space?”. I shall later describe the background for arriving at this notion. For the moment let us accept this question and describe its logic by an analogy with our understanding of space.

From a biological point of view, human beings tend to use physical objects for designating places of interest that often help them representing space and constructing three-dimensional cognitive maps [Egerton, 2005]. The mammalian spatial referencing patterns, as described by Egerton [2005] organise physical objects in the form of a trail, for tracing out specific points in their respective environments. Imagine you were exploring an unknown and complex environment and wanted to find your wayback after an exploration. One solution would be to mark your trail with pebbles. The pebbles would persist and you could readily trace-back your path in return, unless an ill-tempered being removes all the pebbles from your sight after you placed them. Extending this concept, imagine we could mark out any point in space, with pebbles that remain persistent over time. In such a way, we could pin-point an arbitrary location – even a point somewherein front of our eyes – freely in any perspective while tracing out complex paths in all 3 dimensions of space. Extending the idea further, if the pebbles could convey information then they could be used to pass messages or communicate information to other travelers. Further still, if pebbles could express relationships with their neighbors, complex process models could be expressed. Continue reading “AR and its Role in Marking Space”

Parallel Tracking And Global Mapping

It’s been a while since I last blogged as I kept receiving piles and piles of work. I do realize now, that research is not a leisurely activity although it may seem like, for a person who is looking from outside. Apart from usual activities of experiments & literature surveys, doing tutorials, marking assignments, writing conference papers, and making presentations are enough to crush a PhD student to his limits. Nevertheless all these implications help in testifying one’s potential for research and the love for science. So I thought of putting all that matters aside and write a post for the sake of contributing to the scientific knowledge. In particular I’d like to share some of the work I did in my research while taking a short break off from my studies.

Marker-less Augmented Reality has been my primary source of curiosity from the day I started my PhD journey. With my research I am exploring the ways in which we can apply AR into HRI (Human-Robot Interactions) and further improve the collaborative patterns between the man and the robot. Consequently I came up with a state-of-the-art interface based on a well- known marker-less AR platform named PTAMM (Parallel Tracking and Multiple Mapping). The interface that I brought up has the capability for marking an arbitrary point in space persistently with a virtual object (AR object). What does the term persistence mean? Suppose you have an AR object that can be clearly seen through your camera. Now you change the camera perspective, move the camera to a different location and return to your AR object from a different direction.  At this instance you must still see the AR object persistently anchored at its original location. The idea may look simple but systems with such a functionality are still rare, even at the existence of powerful AR frameworks (i.e. PTAM, PTAMM).  This is what I describe as Persistent Augmented Reality. My AR interface provides the capability to appear an AR object persistent over time and space, no matter in which direction you change the camera. See the video below. But how does it work?  What are the concepts? are the questions that you might wonder at this point.

Continue reading “Parallel Tracking And Global Mapping”

PTAM Revealed

ptam_screenshotPTAM (Parallel Tracking & Mapping) is a robust visual SLAM approach developed by Dr. George Klein at Oxford University. It tracks the 3D pose of the camera quite rapidly at frame rate which in turn becomes an ideal platform for implementing marker-less augmented reality. Through this post I’m going to reveal my own insights about PTAM with the help of my hands-on experience with it.

PTAM runs tracking & mapping in two separate threads. Inside the PTAM implementation we can find two files namely, Tracker.cc & MapMaker.cc (NOT the MapViewer.cc). Before start tracking, it demands an initial map of the environment and it was being built by the tracker.  In System.cc there’s function called Run (). The tracking thread runs in this function. In order to build the initial map, user should supply a stereo image pair, particularly on a planar surface. PTAM calculates the initial pose with Homography Matrix, whereas the 3D coordinates of the initial map points were generated with Triangulation. Then the tracker grabs each frame in a tight loop and calculates the camera pose. The tracker performs the pose calculation in following manner. This was implemented inside the TrackFrame() function (Tracker.cc).  Continue reading “PTAM Revealed”

Compiling ARToolkit on Ubuntu 10.04

Apparently I’ve given more thought on to ARToolkit these days  (mainly due to my research), so that it makes me  attempt different things with it. Consequently I’ll be writing a series of posts pertaining to my small experiments for future references. I know it’s pretty boring stuff, talking about a dull subject again and again… but it merely gives us a sensation when doing it physically (particularly when you have nothing left to do 😉 ). In general everybody feels great when their imaginations turn into a physical realization.

ARApplicationInUbuntu

So… enough lecturing & let me keep aside my talking. In today’s post I’ll cover-up the installation of ARToolkit in Ubuntu 10.04. Continue reading “Compiling ARToolkit on Ubuntu 10.04”