Implementación de un módulo de búsqueda de personas dentro de una base de datos de rostros en un ambiente distribuido usando hadoop y los servicios web de amazon (aws).

The digital processing of images take more importance every day. Generally, the algorithms used for processing these images are of high computational complexity caused by the amount of data to process and operations executed on them. For this reason many of these operations involving matrix and vectors calculations, are carried to hardware in the graphics card to not load the processor unit (CPU) and increase performance. This work consists about implementing a module to search for people in a database faces through facial recognition. In its development, we will take advantage about the benefits of distributed processing, provided by the MapReduce programming model and implemented in the Hadoop platform

Constructing a fuzzy grammar for syntactic face detection

This paper presents a structural face detection system. The proposed system consists of three stages; pre-processing, face-components extraction, and final decision-making. In the first stage, image conversion, colour operation, image restoration, and image enhancement are carried out. Face components are extracted in the second stage. A face model is defined, and a fuzzy grammar composed of octal chain codes is used to represent each of the seven face components. The practical limitations of this representation are considered. Structural components are detected, and the possibility degree that the extracted component is a real face component is determined. In the last stage, a commonsense knowledge base is employed for final evaluation. The detected face components and their corresponding possibility degrees allow the human face knowledge base to locate faces in the image and generate a membership degree for that face within the face class. The experimental results obtained using this method are presented

Picture Composition for a Robot Photographer

We explain how to use simple composition rules to drive an automated, mobile photography system. The composition rules are used to determine both the location for a good photograph, and how to frame that photograph. We describe the composition component in the context of a larger application, a robotic photographer. The robot moves around an area with people in it, opportunistically looking for faces and taking photographs. We describe both how to find faces in the world and how to create “good” photographs of those faces

Emergence of categorical face perception after extended early-onset blindness

It is unknown whether the ability to visually distinguish between faces and nonfaces is subject to a critical period during development. Would a congenitally blind child who gains sight several years after birth be able to acquire this skill? This question has remained unanswered because of the rarity of cases of late sight onset. We had the opportunity to work with five early-blind individuals who gained sight late in childhood after treatment for dense bilateral cataracts. We tested their ability to categorize patterns as faces, using natural images that spanned a spectrum of face semblance. The results show that newly sighted individuals are unable to distinguish between faces and nonfaces immediately after sight onset, but improve markedly in the following months. These results demonstrate preserved plasticity for acquiring face/ nonface categorization ability even late in life, and set the stage for investigating the informational and neural basis of this skill acquisition.James S. McDonnell FoundationNational Eye InstituteNick Simons Foundatio

Detecting Faces in Impoverished Images

The ability to detect faces in images is of critical ecological significance. It is a pre-requisite for other important face perception tasks such as person identification, gender classification and affect analysis. Here we address the question of how the visual system classifies images into face and non-face patterns. We focus on face detection in impoverished images, which allow us to explore information thresholds required for different levels of performance. Our experimental results provide lower bounds on image resolution needed for reliable discrimination between face and non-face patterns and help characterize the nature of facial representations used by the visual system under degraded viewing conditions. Specifically, they enable an evaluation of the contribution of luminance contrast, image orientation and local context on face-detection performance

Deficient Human Aspects in Current Multimedia Indexing and Retrieval (MIR) of Large Social Networks Databases

An inside look at the contents of social networks databases shows a significant diversion from traditional database contents and functionality. There is also enormous evidences that Social networks are changing the way multimedia content is shared on the web, by allowing users to upload their photos, videos, and audio content, produced by any means of digital recorders such as mobile/smart-phones, and web/digital cameras. In this article, an overview of multimedia indexing and searching algorithms, following the data growth curve is presented in detail. This paper concludes with the social aspects and new, interesting views on multimedia retrieval in the large social media databases.Keywords: multimedia, indexing, social media, algorithms social networks, databases, retrieva