Integrating Crowdsourcing and Human Computation for Complex Video Annotation Tasks

Video annotation is an activity that aims to supplement this type of multimedia object with additional content or information about its context, nature, content, quality and other aspects. These annotations are the basis for building a variety of multimedia applications for various purposes ranging from entertainment to security. Manual annotation is a strategy that uses the intelligence and workforce of people in the annotation process and is an alternative to cases where automatic methods cannot be applied. However, manual video annotation can be a costly process because as the content to be annotated increases, so does the workload for annotating. Crowdsourcing appears as a viable solution strategy in this con- text because it relies on outsourcing the tasks to a multitude of workers, who perform specific parts of the work in a distributed way. However, as the complexity of required media annoyances increases, it becomes necessary to employ skilled labor, or willing to perform larger, more complicated, and more time-consuming tasks. This makes it challenging to use crowdsourcing, as experts demand higher pay, and recruiting tends to be a difficult activity. In order to overcome this problem, strategies based on the decom- position of the main problem into a set of simpler subtasks suitable for crowdsourcing processes have emerged. These smaller tasks are organized in a workflow so that the execution process can be formalized and controlled. In this sense, this thesis aims to present a new framework that allows the use of crowdsourcing to create applications that require complex video annotation tasks. The developed framework considers the whole process from the definition of the problem and the decomposition of the tasks, until the construction, execution, and management of the workflow. This framework, called CrowdWaterfall, contemplates the strengths of current proposals, incorporating new concepts, techniques, and resources to overcome some of its limitations.

Ownership Identification of Multimedia Content Prediction on a Large Scale

This article prepared with three main objectives, first it is to review the large size of multimedia file protection, second for ownership identification of the multimedia content and finally for implementing this setup for cloud based setup instead of web based service architecture. Therefore many of the infrastructure developed for multimedia content to enable the security against the file handling services for managing the better ownership identification. On private and/or public clouds, the device can be deployed. Our framework has two new components: (i) method of producing 3-D image signatures, and (ii) distributed multimedia object matching engine. The signature method produces stable and accurate 3-D video signatures capturing the depth signals in those videos as well as computationally efficient processing and comparison and having limited space. The corresponding distributed engine is highly scalable and designed to support different multimedia objects. We have introduced and deployed the proposed system on two clouds such as private and amazon based clouds.

Developing Asertive Media Based On Android

This work aimed to develop asertif based on android. Research setting are at Junior High School 3 Godean. Media developed by combine any multimedia object, including text, images, audio, video, and interactive buttons. Content of media such as video to gain understanding about asertif behavior, 15 questions, and social media researcher information. Research method using research and development and alessi and trolip procedures. Research procedure including (1) research plan, (2) design, including flowcart and story board development, (3) development, including media production using code program, alpha, revise, and beta tested. Percentage tested found that content tested 75% (worthy), media tested 81,5% (very worthy). Student tested result 83,6% (very worthy).

Design of Digital Video Watermarking Technique Based on Motion Frames

The availability of high internet bandwidth instantaneously transfer the digital video multimedia object between two or work workstations. Additionally, the advent of digital technology can be mistreating by malicious user to replicate multiple identical copies of the original video illegally. These capabilities introduce the issue of developing the methods for protecting the copyright of video multimedia objects. The proposed technique suggested detecting the motion part of the video by applying heuristic method of histogram difference between two consecutive frames. Then powerful transformations, Singular Value Decomposition (SVD), Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) are used to insert the different segment of the scrambled watermarks into different motion frames of the video. The experimental results show that the scheme is robust to unintentional and intentional video specific attacks which considered being frequently occurring attacks. The proposed algorithm has been contrasted with an existing DWT, DCT or hybrid-based approaches and is found to exhibit better robustness.

Theories of the Soundtrack

This book is concerned with summarizing and critiquing theories of the soundtrack from roughly 1929 until today. A theory of the soundtrack is concerned with what belongs to it, how it is effectively organized, how its status in a multimedia object affects the nature of the object, the tools available for its analysis, and the interpretive regime that the theory mandates for determining the meaning, sense, and structure that sound and music bring to film and other audiovisual media. Beyond that, a theory may also delineate the range of possible uses of sound (and music), classify the types of relations that films have used for image and sound, identify the central problems, and reflect on and describe effective uses of sound in film. This book does not provide an exhaustive historical survey but rather sketches out the range of theoretical approaches that have been applied to the soundtrack over time. For each approach, it presents the basic theoretical framework, considers explicit and implicit claims about the soundtrack, and then works to open the theories to new questions about film sound, often by putting the theories into dialogue with one another. The organization is both chronological and topical: the former in that the chapters move steadily from early film theory through models of the classical system to more recent critical theories; the latter in that the chapters highlight central issues for each generation: the problem of film itself, then of image and sound, then of adequate analytical-descriptive models, and finally of critical-interpretative models.

Multimedia object classification and retrieval

Η παρούσα διατριβή ερευνά το πρόβλημα της ανάκτησης και κατηγοριοποίησης πολυμεσικού περιεχομένου. Στο πρώτο μέρος γίνεται μία διερεύνηση της εφαρμογής Λανθάνουσας Σημασιολογικής Ανάλυσης για ανάκτηση εικόνας σε συλλογές μεγάλης κλίμακας (LSA). Παρουσιάζεται μία αποτελεσματική προσέγγιση για την εφαρμογή LSA η οποία παρακάμπτει την Ανάλυση Ιδιαζουσών Τιμών (SVD) στον πίνακα χαρακτηριστικών, ξεπερνώντας με αυτόν τον τρόπο το πρόβλημα της εφαρμογής της μεθόδου σε σύνολα δεδομένων μεγάλης κλίμακας. Στη μελέτη αυτή διερευνάται ο συνδυασμός διαφορετικών αναπαραστάσεων εικόνας είτε σε πρώιμο στάδιο (Early fusion) είτε σε μεταγενέστερο (Late fusion) με στόχο την αποτελεσματικότερη ανάκτηση εικόνας. Επιπλέον, προτείνεται μία συνάρτηση πυρήνα (Kernel function) βασισμένη στην LSA η οποία συσχετίζει χαρακτηριστικά από διαφορετικές πηγές σε ένα κοινό λανθάνοντα χώρο. Η προτεινόμενη προσέγγιση συνδυάζει την ταξινόμηση με την ανάκτηση, αναπαριστώντας τις εικόνες με ένα σύνθετο διάνυσμα ενσωματώνοντας την πληροφορία που προκύπτει από την κατηγοριοποίηση. Τα πειραματικά αποτελέσματα δείχνουν ότι υπερέχει της λανθάνουσας ευρετηρίασης που προκύπτει από την εφαρμογή SVD.Για την αναπαράσταση εικόνων, προτείνεται μια γενίκευση του μοντέλου Bag-of-Colors (BoC). Ο νέος αλγόριθμος, που αναφέρεται ως QBoC, βασίζεται στην αποσύνθεση των εικόνων σε ένα δέντρο από τεταρτημόρια κωδικοποιώντας με αυτόν τον τρόπο χωρικές πληροφορίες στην τελική απεικόνιση της εικόνας. Σε συνδυασμό με το μοντέλο Bag-of-Visual-Words (BoVW) χρησιμοποιείται για την αποτελεσματική κατηγοριοποίηση ιατρικών εικόνων.Τέλος, παρουσιάζεται μια νέα προσέγγιση για το συνδυασμό του LSA με Νευρωνικά Δίκτυα Συνέλιξης (CNNs) για την ταξινόμηση εικόνων βάση περιεχομένου. Για το σκοπό αυτό, κατασκευάζεται ένας βελτιστοποιημένος λανθάνων σημασιολογικός χώρος που καταγράφει τη συσχέτιση των εικόνων σε κάθε κατηγορία χρησιμοποιώντας ένα προ-εκπαιδευμένο νευρωνικό δίκτυο.Τα χαρακτηριστικά των εικόνων προβάλλονται μέσο ενός σταθμισμένου Latent Semantic Tensor σε ένα χαμηλότερο χώρο και χρησιμοποιούνται για να εκπαιδεύσουν ένα CNN που πραγματοποιεί την τελική ταξινόμηση. Τα πειραματικά αποτελέσματα καταδεικνύουν την αποτελεσματικότητα αυτής της προσέγγισης σε ότι αφορά την ακρίβεια της ταξινόμησης, επιτυγχάνοντας συγκρίσιμα αποτελέσματα με αντίστοιχες σύγχρονες προσεγγίσεις.

2D and 3D Intelligent Watermarking

These days the enormous advancement in the field of data innovation and the wide employments of the web made the security of the information confront a major issue to accomplish the information assurance. The authentication and the copyright of the information is a critical piece of this issue. Scientists started to discover answers for this issue, watermarking and cryptology two of these solutions. Digital watermarking refers to the process of embedding imperceptible information called a digital watermark into a cover multimedia object so that the information may be detected or extracted later for security purposes. Cover multimedia object used to hide watermark information can be any digital media that we used in our daily life for data distribution such as: audio, 2D images, 3D images, and video. The problem that face the researchers in developing a watermarking techniques that the trade of between the impeccability and the robustness of the watermark this chapter focus on how the intelligent algorithms can help in this issue. This chapter surveys the watermarking techniques in 2D and 3D techniques. We conclude that watermarking technique are efficient for different areas of applications.