The Blog's existence -An introspection (I)

Emotion and rational thinking are two sides of a same coin. If I had thought rationally I am sure I would not commenced blogging activity. Running a blog for three years with frequent posts is a small feat. Over the years euphoria of owning a blog vanes and I am pestered for 'deliverable' by my own rational mind. I am in a dilemma whether to have leisure life or pursue passion or work hard for career advancement. This post will unravel my mind and factors that pull (to continue the blog) and push (to windup) me will be elaborated. Hope you enjoy!

Genesis

Blog is concatenation of two words Web and log (weB-LOG). Log is another term for diary. Blog functions as an online diary. Unlike typical diary most of the blogs are thrown open to public for reading and allows viewers to post their comments. In the inception, this blog functioned as an online storehouse of favoured Web links.  Each Web link accompanied a small note for easy reference. Next, articles were written on search keyword (ex. gigapixel camera, SIFT) and Web resources appended in the end of the article. As days progressed number of articles present in the blog increased. Articles exhibited a pattern in style and content. The pattern became a guideline for upcoming posts. Objectives of blog formulated over a period of time.

A thinking man in a moving train          (Image Courtesy: Wikipedia)

Video Indexing and Retrieval

Advancement in digitalization, video technology and communication networks made Internet as a huge repository for text, audio and video documents. In the years to come searching video content in Internet and playing it on a mobile is going to be the norm. Implementation of video search engine poses big challenge because of two reasons. First, size of the video is very big and the next reason is structure of video is not as explicit as text. A text document can be easily broken down i.e. parsed into paragraphs, lines, and words. Much of the video search engine concepts have evolved from text search engine. 

Video Analytics – I

    Today every nook and corner of public place is under surveillance camera. They work round the clock and for 365 days. Thus huge amount of video data is generated. Monitoring a video for more than 20 minutes is tedious to human beings and security officers mostly fail to detect abnormal activities. Thus there is a requirement for “machine assistance” to security officers. Watching video via Internet has become a norm. Popular video servers like YouTube, Dailymotion, and Metacafe provide video free of charge. Netflix is subscription based video server. Sixty hours of video are uploaded every minute in YouTube video servers alone [1]. Thus one can imagine the quantum of video content available in Internet. In the years to come more than half of Internet traffic will be due to video. We encounter problem choosing 'right' or cherry-pick the video from the huge pile of video scattered in Internet. Here to we require some form of “machine assistance” to ordinary viewer.

Video is made up of consecutive sequences of frames or images. Each image contain large amount of pixel information. Images offer very little prior structure to work with [2]. Earlier video databases were small and manual annotation was a possible solution. Today it is not a feasible solution. Present day computing power will manage huge size of data. But automatic analysis of video requires artificial intelligence. Video analytics is the baby step in that direction. Video analytics deals with extraction of information from video with the aid of machine assistance. Video processing means performing some image processing (like resampling or colour correction) on the video content. Most of the time extracted information is overlaid on the video for better human interpretation. Big data analytics is latest buzz word in technical world. Video analytics is considered as a subset of big data analytics.

Eighty years of entertainment video

Let us begin the post with a piece of information. In the Internet more than 50 percentage of traffic is due to video transmission. Colour movies emerged in early 1930s and it was the only source of video at that time. TV emerged in 1950s and added huge collection video to the world. The evolution of video from 1934 to 2014 (80 years) is to be discussed in this post. 

Video Classification

For a general public, a movie stored in video cassette or Video Compact Disc (VCD) is considered as a video. But a graduate in electronics engineering will quantify video as “sequence of still pictures (frames) that are displayed on screen in a very small time interval.” Video can be classified into three major categories namely; entertainment video, Industrial video and Surveillance video. As name implies entertainment video encompasses movies and TV programmes. As per the definition Black and White (B&W) silent movies come under the category of video.  But in this post it is restricted to colour talkies (colour movie with soundtrack). In manufacturing industries video cameras are extensively used to capture the production processes. Videos are analysed and features are extracted. These features are used as feedback in production processes. Machines fitted with camera replace human beings. They work 24x7, seven days a week without a holiday. As they don't require any pay rise, there is no strike in factories. The video content generated by machine vision systems can be branded as Industrial video. Most of the public places are monitored by a surveillance system. This cost effective method reduces the requirement of Beat Officers (police who are on patrol), aftermath of crime recorded video acts as clues to nail the culprits and acts as prosecution evidence in the court of law. Video content is increasing leaps and bounds. 

Gigapixel Images

A 1.8 gigapixel video surveillance camera named ARGUS was built jointly by DARPA (Defense Advanced Research Projects Agency) and the US Army. It is capable to pick out a sleeping dog in the Earth from the altitude of 20,000 feet (6 km).  In other words, it can resolve details as close to six inches. Quite amazing! The ARGUS can be attached to drone (unmanned aeroplane remotely controlled) and taken to a height of 20,000 feet to observe 25 square kilometres at any instant. Thus entire New York City can be brought into surveillance by two ARGUS attached drones to hover over the city.  The entire Manhattan is under observation 24x7.  

Like ARGUS, AWARE-2 is another gigapixel camera. It was used to study the behaviour of tundra swans present in Pungo Lake, USA [1]. With AWARE-2 camera gigapixel snapshot was taken [1] and found 656 swans swimming in the lake and 27 flying above the lake at that instant. Scientists can use the snapshot to track individual swan or study the swans' flock (group) behaviour.  Existing scanning panoramic camera cannot achieve this feat. Use of gigapixel is not confined to ecology alone. It can be applied in fields like urban planning, traffic control, forestry, archaeology and so on.

Gigapixel snapshot of Budapest city, Hungary. Inset: two landmarks building in the city. Zooming operation  on gigapixel image helps us find the buildings. Image courtesy www.photographyblog.com [7]