BREMOND , François

Data association and fusion is pivot for object trackingin multi-camera network. We present a novel frameworkfor solving online multi-object tracking in partially overlappingmulti-camera network by modelling tracklet associationas combinatorial optimization problem hypothesizedon ensemble of cues such as appearance, motion and...

Automatic detection and analysis of human activities captured by various sensors (e.g. 1 sequence of images captured by RGB camera) play an essential role in various research fields in order 2 to understand the semantic content of a captured scene. The main focus of the earlier studies has 3 been widely on supervised classification problem,...

There is major interest nowadays in Moderate-High Intensity Aerobic Activities for non-pharmacological interventions in elderly suffering from neurodegenerative diseases like Alzheimer'sDisease and Related Disorders [1]. Within the context of the development of serious games forthis population, we have developed algorithms to...

The present year witnesses another milestone in Pedestrian detection's journey: it has achieved remarkable progresses in the course of the past 15 years, and experts foresee an everyday use of numerous stemming applications within the next 15. Standing on the tipping point between yesterday and tomorrow pushes to the field's retrospect....

Ce chapitre n'engage que ses auteurs et non pas leurs institutions qui ont leur propre comité d'éthique (non consulté pour cette contribution). Ce texte a pour objectif d'aborder les enjeux du débat éthique quant à l'utilisation des Technologies de l'Information pour limiter les effets de la Maladie d'Alzheimer. Ce texte est ainsi l'occasion de...

The person re-identification problem is a well known retrieval task that requires finding a person of interest in a network of cameras. In a real-world scenario, state of the art algorithms are likely to fail due to serious perspective and pose changes as well as variations in lighting conditions across the camera network. The most effective...

In video-based person re-identification, while most work has focused on problems of person signature representation and matching between different cameras, intra-sample variance is also a critical issue to be addressed. There are various factors that cause the intra-sample variance such as detection/tracking inconsistency, motion change and...

Motion is a strong clue for unsupervised grouping of individuals in a crowded environment. We show that collective motion in the crowd can be discovered by temporal analysis of points trajectories. First k-NN graph is constructed to represent the topological structure of point trajectories detected in crowd. Then the data-driven graph...

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...

Sensitivity to scene such as contrast and illumination intensity, is one of the factors significantly affecting the performance of object trackers. In order to overcome this issue, tracker parameters need to be adapted based on changes in contextual information. In this paper, we propose an intelligent mechanism to adapt the tracker parameters,...

Les Serious Game (SG) figurent, à ce jour, parmi les mesures non médicamenteuses au bénéfice des personnes âgées, permettant de préserver une bonne santé dans des conditions ludiques, en effectuant des entraînements physiques et cognitifs. Néanmoins, la question de la motivation de cesutilisateurs particuliers reste encore à étudier. En effet,...

— Serious Game is considered currently as a new non-medicated measure to the advantage of seniors, allowing to maintain good health in the playful conditions by doing cognitive and physical exercises. However, user's motivation is still a problem that needs to be studied more precisely. Indeed, most of them previously have neither game culture...

In this paper, we study how different skeleton extraction methods affect the performance of action recognition. As shown in previous work skeleton information can be exploited for action recognition. Nevertheless, skeleton detection problem is already hard and very often it is difficult to obtain reliable skeleton information from videos. In...

Serious Games offer a new way to older adults to improve various abilities such as the vision, the balance or the memory. However, cognitive impairment causes a lot of difficulties to them when actively practicing these games. Their engagement and motivation are reduced rapidly when encountering successive problems without any help. In this...

Achieving high detection accuracy and high inference speed is important for a pedestrian detection system in self-driving applications. There exists a trade-off between detection accuracy and inference speed in modern convolu-tional object detectors. In this paper, we propose a novel pedestrian detection system, which leverages spatial...

Existing surveillance systems for older people activity analysis are focused on video and sensors analysis (e.g., accelerometers, pressure, infrared) applied for frailty assessment, fall detection, and the automatic identification of self-maintenance activities (e.g., dressing, self-feeding) at home. This paper proposes a multi-sensor...

Older people with dementia have many difficulties while using Serious Game for their cognitive training. Besides of the lack of game culture and a limited acceptance toward new technology, memory and cognitive disorders influence negatively also on their performance. We propose a virtual agent that can enhance performance of player using...

This paper presents an unsupervised approach for learning long-term human activities without requiring any user interaction (e.g., clipping long-term videos into short-term actions, labeling huge amount of short-term actions as in supervised approaches). First, important regions in the scene are learned via clustering trajectory points and the...

Many supervised approaches report state-of-the-art results for recognizing short-term actions in manually clipped videos by utilizing fine body motion information. The main downside of these approaches is that they are not applicable in real world settings. The challenge is different when it comes to unstructured scenes and long-term videos....

Appearance based multi-object tracking (MOT) is a challenging task, specially in complex scenes where objects have similar appearance or are occluded by background or other objects. Such factors motivate researchers to propose effective trackers which should satisfy real-time processing and object trajectory recovery criteria. In order to...

This paper proposes BEHAVE, a person-centered pipeline for probabilistic event recognition. The proposed pipeline firstly detects the set of people in a video frame, then it searches for correspondences between people in the current and previous frames (i.e., people tracking). Finally, event recognition is carried for each person using...

In this paper, we address the detection of daily living activities in long-term untrimmed videos. The detection of daily living activities is challenging due to their long temporal components, low inter-class variation and high intra-class variation. To tackle these challenges, recent approaches based on Temporal Convolutional Networks (TCNs)...

In video surveillance, Person Re-Identification(Re-ID) consists in recognizing an individual who has already been observed (hence the term Re-Identification) over a network of cameras. Usually, the person Re-Id system is divided into two stages: i)constructing a person's appearance signature by extracting feature representations which should be...

Characterizing an image region by its feature inter-correlations is a modern trend in computer vision. In this paper, we introduce a new image descriptor that can be seen as a natural extension of a covariance descriptor with the advantage of capturing nonlinear and non-monotone dependencies. Inspired from the recent advances in mathematical...