DOI 10.4010/2016.647 ISSN 2321 3361 © 2016 IJESC Research Article Volume 6 Issue No. 3 Video Content Analysis for Assessment of the Advertisement Jigar Gajjar1, Aayush Khator2, Pooja Patil3 Department of Computer Engineering Mumbai University, Vidyalankar Institute of Technology, India. [email protected], [email protected], [email protected] Abstract: This paper is a literature survey paper of our system which will help advertisers to get some sort of feedback about their advertisement. Advertisement is a form communication which helps to promote a product in an attempt to induce consumers purchase that product. Advertisement are basically displayed to increase the awareness about brands that are introduced in the market or to demonstrate the differences between the products available and the competing products in order to increase their sell.Advertisement helps to get insight of the product. Now a days billboards are preferred to display advertisements in malls. Billboards are effective way of advertising as they are more attractive and noticeable. However it is not possible for advertisers to know the public response for those ads on the billboards thus creating a bottleneck. Our system helps in getting some chunk of that response from the people who are interested in the displayed ads and crunching that data to give advertisers a true feedback for their ads on the billboard. This system includes real-time detection of multiple faces and tracking of those detected faces which will be used to calculate the amount of time person spends in front of the given billboard. It also includes nose and eyes tracking to know whether the viewer's attention is at billboard or outside it. We will be even using calibrated stereo camera for depth estimation that is for knowing at what distance is the viewer from the camera. The timer will be implemented to know time spent by individual in front of the billboard. The data is being analyzed and converted in the form of statistics and visual information such as graphs to provide advertisers valuable feedback for their ads. The statistics which will be viewed after number of faces being detected and time average evaluation for each face which will help the advertiser with the scope of improvement in the advertisement and increase in profit. Index Term: Billboard, Calibrated stereo camera, Depth estimation, Face detection and tracking, In and Out algorithm, Timer, Viewer’s attention based on head pose estimation. I. INTRODUCTION. advertisement or announcement, a billboard is usually found Advertising is a form of communication which helps outdoors along roadways, malls etc where number of people people to know about the new products or services in the visit is large in number. Advantage of displaying market and help them to purchase the better ones by giving advertisement through billboards is it is more noticeable and the overview of the product. It plays a vital role in deciding reaches to large number of people as it is large in size and the growth of the company by means of sale, production, displayed in public places. Billboard advertisement can be revenue, popularity etc. Shopping centres, malls offer vast, placed wherever we feel it will have the high impact. This can often untapped opportunities to earn money by advertising be a huge advantage when we have a business we want to products, brands, services etc. As likely said malls are the draw traffic to rightly by some other path, or we have a shop better places to advertise because it does not emphasize only just down the road. on limited products but give user the exposure to numerous other products by making a variety of options available. Advertising is the way for advertiser to get engaged with the consumers on the issues related to product by detailing it. It can help to build trust between the customer and the product. Advertising is being viewed as a technique of mass promotion in which single message can reach to large number of people. Advertising is also being considered a one-way technique of marketing where the customer is not in position to immediately respond to the advertisement. If you want your advertisement to hit on the day a product launches or event is about to happen, this is the only vehicle you control completely. Advertisements are in various forms such as emails, newspapers, web pages, radio, television, magazines. Fig 1: System Overview Outdoor advertisements are actually the ones which reach to large number of people and can easily catch the attention of Nowadays billboards are the most trending ways to display an the person passing by it. They are displayed outdoor on roads, advertisement in malls because of its visual impact on the malls etc. Outdoor advertisements are in the form of user. Billboards are more appealing and make your hoardings, posters, billboards, electronic displays etc. A flat advertising more noticeable. This motivated us to develop a panel or we can call it as a board that holds some kind of International Journal of Engineering Science and Computing, March 2016 2775 http://ijesc.org/ system that helps them understand the response of the user to where they spend the maximum time in the store, when and the billboards placed in malls and in turn help them to what they shop and what they look at are all tools that help in understand the needs and interests of the onlooker. Face maximizing the retailer’s targeting efforts and profits, thus, detection of human facial features like the mouth, nose and improving their business. In addition, mostly ads displayed on eyes in a given video we can estimate the time spent by a user screens in and out of stores are not effective in reaching their in viewing the advertisement. For detection of multiple faces target audiences. Retailers can increase their profits if they can we will be using Viola-Jones algorithm [1]. We will be automatically target their customers’ with the most suited adapting a multi-step process in order to achieve the goal. advertisement.” TruMedia offered their customers a solution Once the face is being detected we will use KLT algorithm to analyse customer profile and behaviour in key retail areas. [2][3] for tracking the face. First the camera detects the multiple The solution is a completely innovative and futuristic solution faces and then captures the feature points. Further this features that provides answers to the retailer’s need to understand and points are being tracked. We will be detecting nose, eye and target his end audiences. The solution combines people mouth. We will estimate the geometric centre and get the counting with demographic measurement functionalities. As a centre coordinates. By using this will track nose, eye and result, the retailer is provided with information about his mouth centres to estimate head pose. We will be using customers like the age group and gender, and what they saw in calibrated stereo cameras for depth estimation in which we the store and for how long they looked. In addition, what is would be determining the viewer from the billboard is how the total number of customers entering the store along with far. After this we will be using our own developed algorithm their distribution throughout the day for each store. known as In and out algorithm which we are using to figure III. Related work out whether the person is looking inside the billboard for reading or looking outside the billboard. Further we will be In the last few years, there are many algorithms also using timer which helps us by giving time for how long developed for face detection and tracking, for face detection the person was looking at the billboard content. The timer will and tracking. The existing face detection methods can be be on as soon as the face is being tracked as goes off when our categorized as feature based approach and image based algorithms stop tracing face. With this information and the approach. Feature based approach requires some beforehand timers available, we get the data which is analysed and then data about faces. It makes use of facial features which the statistical reports are given to the advertisers. This includes colour, shape and component feature. Whereas, statistics will increase the scope of improvement. A good image based approach categorizes face without face without advertisement helps one to boost their profit because the good any prior knowledge about face. It feeds facial features into advertisement will draw in many new customers in their system through training. The breakthrough in face detection business. algorithms happened through Viola-Jones. It was a boon for face detection or face recognition systems. "Robust Real-Time II. Literature Survey Face Detection"[1], the paper by the inventors itself Paul Viola and Michael J. Jones have given detailed explanation of Face detection is a process to determine whether there how Viola-Jones face detection algorithm. Given as input is any face present in an image or video. Face detection is not faces and non faces it is trained to detect faces. There are three an easy process as many external and internal factors affect key contribution [1], integral image which allows the features the detection. Once the face is detected it opens the gate for a used by Viola-Jones detector to be computed quickly. Cascade wide range of information say for example one can determine which uses different stages for identifying features quickly how long a person was looking at the camera, their emotions and classify the face as face or non-face. Adaboost removes and even their gender. Some of the recent works on the redundant features or irrelevant features.