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Identity safekeeping on chats has recently become an important problem on social networks. One of the most important issues is identity theft, where impostors steal the identity of a person, substituting her in the chats, in order to have access to private information. In the literature, the problem has been addressed by designing sets of features which capture the way a person interacts through the...
We propose a novel video event retrieval algorithm given a video query containing grouped events from large scale video database. Rather than looking for similar scenes using visual features as conventional image retrieval algorithms do, we search for the similar semantic events (e.g. finding a video such that a person parks a vehicle and meets with other person and exchanges a bag). Videos are analyzed...
Locality sensitive hashing (LSH) is a computationally efficient alternative to the distance based anomaly detection. The main advantages of LSH lie in constant detection time, low memory requirement, and simple implementation. However, since the metric of distance in LSHs does not consider the property of normal training data, a naive use of existing LSHs would not perform well. In this paper, we...
This paper is aimed at presenting a new virtual camera model which can efficiently model refraction through flat housings in underwater photography. The key idea is to employ a pixel-wise virtual focal length concept to encode the refractive projection inside the flat housing. The radially-symmetric structure of the varifocal length around the normal of the housing surface allows us to encode the...
This paper discusses the usefulness of human body-parts tracking for acquiring subtle cues in social interactions. While many kinds of body-parts tracking algorithms have been proposed, we focus on particle filtering-based tracking using prior models, which have several advantages for researches on social interactions. As a first step for extracting subtle cues from videos of social interaction behaviors,...
We present a novel Markov Random Field (MRF) structure-based approach to the problem of facial action unit (AU) intensity estimation. AUs generally appear in common combinations, and exhibit strong relationships between the intensities of a number of AUs. The aim of this work is to harness these links in order to improve the estimation of the intensity values over that possible from regression of...
This paper introduces Cubistic Representation as a novel 3D surface shape model. Cubistic representation is a set of 3D surface fragments, each fragment contains subject's 3D surface shape and its color and redundantly covers the subject surface. By laminating these fragments using a given pose parameter, the subject's appearance can be synthesized. Using cubistic representation, we propose a real-time...
In this paper we present a method for local processing of photos and associated sensor information on mobile devices. Our goal is to lay the foundations of a collaborative multi-user framework where ad-hoc device groups can share their data around a geographical location to produce more complex composited views of the area, without the need of a centralized server-client - cloud-based - architecture...
This paper proposes a novel image parsing framework to solve the semantic pixel labeling problem from only label strokes. Our framework is based on a network of voters, each of which aggregates both a self voting vector and a neighborhood context. The voters are parameterized using sparse convex coding. To efficiently learn the parameters, we propose a regularized energy function that propagates label...
Detection and recognition of collective human activities are important modules of any system devoted to high level social behavior analysis. In this paper, we present a novel semantic-based spatio-temporal descriptor which can cope with several interacting people at different scales and multiple activities in a video. Our descriptor is suitable for modelling the human motion interaction in crowded...
Image and video classification is a challenging task, particularly for complex real-world data. Recent work indicates that using multiple features can improve classification significantly, and that score fusion is effective. In this work, we propose a robust score fusion approach which learns non-linear score calibrations for multiple base classifier scores. Through calibration, original base classifiers...
Action recognition is an important precursor for understanding human activities in videos. The current paradigm of action recognition is to classify a video sequence as a whole. However, actions usually occur only in part of a video sequence, rendering the rest of the video irrelevant for action recognition. In this paper, we propose a method for learning a subsequence classifier which can detect...
This paper addresses the background estimation problem for videos captured by moving cameras, referred to as video grounding. It essentially aims at reconstructing a video, as if it would be without foreground objects, e.g. cars or people. What differentiates video grounding from known background estimation methods is that the camera follows unconstrained motion so that background undergoes ongoing...
Until recently, inference on fully connected graphs of pixel labels for scene understanding has been computationally expensive, so fast methods have focussed on neighbour connections and unary computation. However, with efficient CRF methods for inference on fully connected graphs, the opportunity exists for exploring other approaches. In this paper, we present a fast approach that calculates unary...
This paper proposes a methodology to estimate the transmission in underwater environments which consists on an adaptation of the Dark Channel Prior (DCP), a statistical prior based on properties of images obtained in outdoor natural scenes. Our methodology, called Underwater DCP (UDCP), basically considers that the blue and green color channels are the underwater visual information source, which enables...
In this paper, we propose to separate diffuse and specular reflection components for color images in the HSI color space. Under white illumination, pixels with the same diffuse chromaticity have the same hue. Meanwhile, specular pixels have lower saturations than the diffuse ones. Based on these properties, separating reflection components can be achieved by adjusting saturations of specular pixels...
We propose a polarization-based method to enhance the visibility of an image by canceling the haze effect. Haze is a natural phenomenon that degrades the visibility of a scene. Aerosols in air reflect sunlight and cause polarization. Therefore, we analyze the polarization state of the observed light to remove the haze effect from a captured image. Our approach is to use two reference objects that...
In this paper, we propose a novel image representation method by using multi-band projectors. In this image representation method, each observer, such as human, camera and other sensors, can perceive different images from each other, even if the image projected from the projector is identical. For this objective, we encode multiple images into a single image by using the difference of spectral sensitivity...
Knowing the RGB spectral sensitivities of a camera is useful for several image processing applications. However, camera manufacturers seldom provide this information. Calibration methods for determining them can be daunting, requiring either sophisticated instruments or carefully controlled lighting. This paper presents a quick and easy method that provides a reasonable approximation of the camera...
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