Automatic genre identification for content-based video categorization

This paper presents a set of computational features originating from our study of editing effects, motion, and color used in videos, for the task of automatic video categorization. These features besides representing human understanding of typical attributes of different video genres, are also inspired by the techniques and rules used by many directors to endow specific characteristics to a genre-program which lead to certain emotional impact on viewers. We propose new features whilst also employing traditionally used ones for classification. This research, goes beyond the existing work with a systematic analysis of trends exhibited by each of our features in genres such as cartoons, commercials, music, news, and sports, and it enables an understanding of the similarities, dissimilarities, and also likely confusion between genres. Classification results from our experiments on several hours of video establish the usefulness of this feature set. We also explore the issue of video clip duration required to achieve reliable genre identification and demonstrate its impact on classification accuracy.<br /

Scene extraction in motion pictures

This paper addresses the challenge of bridging the semantic gap between the rich meaning users desire when they query to locate and browse media and the shallowness of media descriptions that can be computed in today\u27s content management systems. To facilitate high-level semantics-based content annotation and interpretation, we tackle the problem of automatic decomposition of motion pictures into meaningful story units, namely scenes. Since a scene is a complicated and subjective concept, we first propose guidelines from fill production to determine when a scene change occurs. We then investigate different rules and conventions followed as part of Fill Grammar that would guide and shape an algorithmic solution for determining a scene. Two different techniques using intershot analysis are proposed as solutions in this paper. In addition, we present different refinement mechanisms, such as film-punctuation detection founded on Film Grammar, to further improve the results. These refinement techniques demonstrate significant improvements in overall performance. Furthermore, we analyze errors in the context of film-production techniques, which offer useful insights into the limitations of our method

Finding the optimal temporal partitioning of video sequences

The existing techniques for shot partitioning either process each shot boundary independently or proceed sequentially. The sequential process assumes the last shot boundary is correctly detected and utilizes the shot length distribution to adapt the threshold for detecting the next boundary. These techniques are only locally optimal and suffer from the strong assumption about the correct detection of the last boundary. Addressing these fundamental issues, in this paper, we aim to find the global optimal shot partitioning by utilizing Bayesian principles to model the probability of a particular video partition being the shot partition. A computationally efficient algorithm based on Dynamic Programming is then formulated. The experimental results on a large movie set show that our algorithm performs consistently better than the best adaptive-thresholding technique commonly used for the task

Determining dramatic intensification via flashing lights in movies

Movie directors and producers worldwide, in their quest to narrate a good story that warrants repeated audience viewing, use many cinematic elements to intensify and clarify the viewing experience. One such element that directors manipulate is lighting. In this paper we examine one aspect of lighting, namely flashing lights, and its role as an intensifier of dramatic effects in film. We present an algorithm for robust extraction of flashing lights and a simple mechanism to group detected flashing lights into flashing light scenes and analyze the role of these segments in story narration. In addition, we demonstrate how flashing lights detection can improve the performance of shot-based video segmentation. Experiments on a number of video sequences extracted from real movies yields good results. Our technique detects 90.4% of flashing lights. The detected flashing lights correctly eliminates 92.7% of false cuts in these sequences. In addition, data support is compiled to demonstrate the association between flashing light scenes and certain dramatic intensification events such as supernatural power, crisis or excitement.<br /

Impact of Environmental Hazards on Sense of Vision - A Conceptual Study

“Eyes are god’s greatest gift and are said to be the best among all sense organs.” We perceive upto 80% of all impressions by means of our sight. The eye is a specialized sense organ that helps us to understand our environment, which is sensitive to light and atmospheric pressure, therefore its functions, to a large extent depend on the quality of the environment. Eyes being the window to the world, but for many the view become blur, dim and even entirely dark due to visual impairment that can be due to environmental contacts. Although the full impact of the environment on sight is unknown, many reports have shown that low vision and blindness can be directly or indirectly related to environmental exposure. In this article ayurvedic view on the topic is enlighted along with Kriyakalpa procedures

Study on analysis of Nidana and Samprapti in Diabetic Retinopathy (Pramehaja Timira)

India is set to emerge as the Diabetic capital of the world. Diabetic retinopathy (DR) occurs due to diabetic complication that effects or damages the blood vessels of light sensitive tissue of the retina. It is also observed that patients who have diabetes more than 10 years show some form of DR. Prevalence in India ranges from 17.6 - 28.2%. According to Ayurveda in Netra Prakashika - Shri Pujyapada Mahamuni, mentioned Madhumeha as a cause for Netraroga. DR can be termed as Madhumehajanya Timira. Avarana and Dhatukshaya have important role in development of DR due to prolonged and uncontrolled hyperglycemia. All the tridosha along with Rakta Dosha and Saptadhatu with four internal Dristipatala of eye are effected in Pramehaja Timira in different stages of disease. In the early stages of diabetic retinopathy there may be minimal symptoms. As condition progresses, DR symptoms may include like floaters, blurred vision and visionloss. There are two types of diabetic retinopathy: Early DR and Advanced DR. The longer period having diabetes and the less controlled blood sugar, are more likely to develop with this eye complication. Hereby an attempt is made in this article to understand the Nidana and samprapthi which leads to madhumehaja Timira which can be considered as a silent killer of vision

Improved fade and dissolve detection for reliable video segmentation

We present improved algorithms for automatic fade and dissolve detection in digital video analysis. We devise new two-step algorithms for fade and dissolve detection and introduce a method for eliminating false positives from a list of detected candidate transitions. In our detailed study of these gradual shot transitions, our objective has been to accurately classify the type of transitions (fade-in, fade-out, and dissolve) and to precisely locate the boundary of the transitions. This distinguishes our work from early work in scene change detection which focuses on identifying the existence of a transition rather than its precise temporal extent. We evaluate our algorithms against two other commonly used methods on a comprehensive data set, and demonstrate the improved performance due to our enhancements

Identifying film takes for cinematic analysis

In this paper, we focus on the &lsquo;reverse editing&rsquo; problem in movie analysis, i.e., the extraction of film takes, original camera shots that a film editor extracts and arranges to produce a finished scene. The ability to disassemble final scenes and shots into takes is essential for nonlinear browsing, content annotation and the extraction of higher order cinematic constructs from film. In this work, we investigate agglomerative hierachical clustering methods along with different similarity metrics and group distances for this task, and demonstrate our findings with 10 movies.<br /

Neighborhood coherence and edge based approaches to film scene extraction

In order to enable high-level semantics-based video annotation and interpretation, we tackle the problem of automatic decomposition of motion pictures into meaningful story units, namely scenes. Since a scene is a complicated and subjective concept, we first propose guidelines from film production to determine when a scene change occurs in film. We examine different rules and conventions followed as part of Film Grammar to guide and shape our algorithmic solution for determining a scene boundary. Two different techniques are proposed as new solutions in this paper. Our experimental results on 10 full-length movies show that our technique based on shot sequence coherence performs well and reasonably better than the color edges-based approach

Film grammar based refinements to extracting scenes in motion pictures

To enable high-level semantic indexing of video, we tackle the problem of automatically structuring motion pictures into meaningful story units, namely scenes. In our recent work, drawing guidance from film grammar, we proposed an algorithmic solution for extracting scenes in motion pictures based on a shot neighborhood color coherence measure. In this paper, we extend our work by presenting various refinement mechanisms, inspired by the knowledge of film devices that are brought to bear while crafting scenes, to further improve the results of the scene detection algorithm. We apply the enhanced algorithm to ten motion pictures and demonstrate the resulting improvements in performance.<br /