BILINSKI , Piotr

The bag-of-words approach with local spatio-temporal features have become a popular video representation for action recognition. Recent methods have typically focused on capturing global and local statistics of features. However, existing approaches ignore relations between the features, particularly space-time arrangement of features, and thus...

The bag-of-words approach with local spatio-temporal features have become a popular video representation for action recognition in videos. Together these techniques have demonstrated high recognition results for a number of action classes. Recent approaches have typically focused on capturing global statistics of features. However, existing...

In this paper, we propose a new local spatio-temporal descriptor for videos and we propose a new approach for action recognition in videos based on the introduced descriptor. The new descriptor is called the Video Covariance Matrix Logarithm (VCML). The VCML descriptor is based on a covariance matrix representation, and it models relationships...

Recently, local descriptors have drawn a lot of attention as a representation method for action recognition. They are able to capture appearance and motion. They are robust to viewpoint and scale changes. They are easy to implement and quick to calculate. Moreover, they have shown to obtain good performance for action classification in videos....

In this paper, we focus on the important topic of violence recognition and detection in surveillance videos. Our goal is to determine if a violence occurs in a video (recognition) and when it happens (detection). Firstly, we propose an extension of the Improved Fisher Vectors (IFV) for videos, which allows to represent a video using both local...

Body height, weight, as well as the associated and composite body mass index (BMI) are human attributes of pertinence due to their use in a number of applications including surveillance, re-identification, image retrieval systems, as well as healthcare. Previous work on automated estimation of height, weight and BMI has predominantly focused on...

The recognition in real time of crowd dynamics in public places are becoming essential to avoid crowd related disasters and ensure safety of people. We present in this paper a new approach for Crowd Event Recognition. Our study begins with a novel tracking method, based on HOG descriptors, to finally use pre-defined models (i.e. crowd...

This paper presents a novel and unsupervised approach for discovering "sudden" movements in video surveillance videos. The proposed approach automatically detects quick motions in a video, corresponding to any action. A set of possible actions is not required and the proposed method successfully detects potentially alarm-raising actions without...

We present an algorithm for tracking multiple objects through occlusions. Firstly, for each detected object we compute feature points using the FAST algorithm [1]. Secondly, for each feature point we build a descriptor based on the Histogram of Oriented Gradients (HOG) [2]. Thirdly, we track feature points using these descriptors. Object...

Automated gender estimation has numerous applications including video surveillance, human computer-interaction, anonymous customized advertisement and image retrieval. Most commonly, the underlying algorithms analyze facial appearance for clues of gender. In this work, we propose a novel approach for gender estimation, based on facial behavior...

Recent development in affordable depth sensors opens new possibilities in action recognition problem. Depth information improves skeleton detection, therefore many authors focused on analyzing pose for action recognition. But still skeleton detection is not robust and fail in more challenging scenarios, where sensor is placed outside of optimal...

Creating realistic human videos entails the challenge of being able to simultaneously generate both appearance, as well as motion. To tackle this challenge, we introduce G 3 AN, a novel spatio-temporal generative model, which seeks to capture the distribution of high dimensional video data and to model appearance and motion in disentangled...

This paper addresses a problem of recognizing human actions in video sequences. Recent studies have shown that methods which use bag-of-features and space-time features achieve high recognition accuracy. Such methods extract both appearance-based and motion-based features. This paper focuses only on appearance features. We proposeto model...

This paper addresses the problem of recognizing human actions in video sequences for home care applications. Recent studies have shown that approaches which use a bag-of-words representation reach high action recognition accuracy. Unfortunately, these approaches have problems to discriminate similar actions, ignoring spatial information of...

Generating human videos based on single images entails the challenging simultaneous generation of realistic and visual appealing appearance and motion. In this context, we propose a novel conditional GAN architecture, namely ImaGINator, which given a single image, a condition (la-bel of a facial expression or action) and noise, decomposes...

Recognizing expressions in severely demented Alzheimer's disease (AD) patients is essential, since such patients have lost a substantial amount of their cognitive capacity, and some even their verbal communication ability (e.g., aphasia). This leaves patients dependent on clinical staff to assess their verbal and non-verbal language, in order...

We propose a method for the synthesis of the magnitudes of Head-related Transfer Functions (HRTFs) using a sparse representation of anthropometric features.Our approach treats the HRTF synthesis problem as finding a sparse representation of the subject's anthropometric features w.r.t. the anthropometric features in the training set.The...

The elderly population has been growing dramatically and future predictions and estimations showcase that by 2050 the number of people over 65 years old will increase by 70%, the number of people over 80 years old will increase by 170%, outnumbering younger generations from 0-14 years. Other studies indicate that around half of the current...

Assessing facial dynamics in patients with major neurocogni-tive disorders and specifically with Alzheimers disease (AD) has shown to be highly challenging. Classically such assessment is performed by clinical staff, evaluating verbal and non-verbal language of AD-patients, since they have lost a substantial amount of their cognitive capacity,...