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Person reidentification is a problem of recognizing a person across non-overlapping camera views. Pose variations, illumination conditions, low resolution images, and occlusion are the main challenges encountered in reidentification. Due to the uncontrolled environment in which the videos are captured, people could appear in different poses and due to which the appearance of a person could vary significantly...
Human detection is a key functionality to reach Human Robot/Computer Interaction. The human tracking is also a rapidly evolving area in computer and robot vision; it aims to explore and to follow human motion. We present in this article an intelligent system to learn human detection. The descriptors used in our system make up the combination of HOG and SIFT that capture salient features of humans...
The capability to visually discern possible obstacles from the sky would be a valuable asset to a UAV for avoiding both other flying vehicles and static obstacles in its environment. The main contribution of this article is the presentation of a feasible approach to obstacle avoidance based on the segmentation of camera images into sky and non-sky regions. The approach is named the Sky Segmentation...
When persons interact, non-verbal cues are used to direct the attention of persons towards objects of interest. Achieving joint attention this way is an important aspect of natural communication. Most importantly, it allows to couple verbal descriptions with the visual appearance of objects, if the referred-to object is non-verbally indicated. In this contribution, we present a system that utilizes...
Robotic vehicles operating in outdoor environments, commonly referred to as unmanned ground vehicles (UGV), are confronted with unstructured/semi-structured environments that are variable in nature. The geographical location significantly influences the environment's appearance, there are longer term seasonal cycles, as well as immediate affects such as the weather and lighting conditions. This environmental...
Robot learning by imitation has become a key topic in robotics research in the last years, due to the increasing interest in social robots. While several architectures that deal with this topic have been proposed, few efforts have been done in finding unified formats that may help in analyzing and comparing these architectures. This paper firstly proposes a set of components that can be identified...
This paper introduces a new approach in automatic attendance management systems, extended with computer vision algorithms. We propose using real time face detection algorithms integrated on an existing Learning Management System (LMS), which automatically detects and registers students attending on a lecture. The system represents a supplemental tool for instructors, combining algorithms used in machine...
This paper describes a robotic system that learns visual models of symmetric objects autonomously. Our robot learns by physically interacting with an object using its end effector. This departs from eye-in-hand systems that move the camera while keeping the scene static. Our robot leverages a simple nudge action to obtain the motion segmentation of an object in stereo. The robot uses the segmentation...
This paper proposes cooking support using ubiquitous sensors. We developed a machine learning algorithm that recognizes cooking procedures by taking into account widely varying sensor information and user behavior. To provide appropriate instructions to users, we developed a Markov-model-based behavior prediction algorithm. Using these algorithms, we developed cooking support automatically displaying...
This paper presents an algorithm based on the method of supervised machine learning and multi-keyframes to achieve markerless augmented reality (AR) application when there is a locally planar object in the scene. The main goal is to solve the problem of AR tracking in outdoor environment by only using vision and natural features. Instead of tracking fiducial markers, we track natural keypoints, during...
In this paper a novel method for view independent human movement representation and recognition, exploiting the rich information contained in multi-view videos, is proposed. The binary masks of a multi-view posture image are first vectorized, concatenated and the view correspondence problem between train and test samples is solved using the circular shift invariance property of the discrete Fourier...
In this paper, we propose cooking support system by using ubiquitous sensors. We developed machine learning algorithm that recognizes cooking procedures by taking account of various and numerous sensor information and past human behaviors. In order to provide appropriate instructions to a user, we also developed Markov-model based human behavior prediction algorithm. By employing these algorithms,...
This paper critically evaluates existing work, presents an opinion mining framework and exposes new areas of research in opinion mining. Individuals, businesses and government can now easily know the general opinion prevailing on a product, company or public policy. At the core of this field is semantic orientation of subjective terms in documents or reviews which seeks to establish their contextual...
Machine learning algorithms can be used to discover patterns in data into e-commerce C2C portals and this knowledge can then be useful to help customers to refine their searches and to choose what to buy. In this work, it is proposed a new machine learning algorithm based on fuzzy logic. We describe the proposed algorithm for supporting customer searches in e-marketplaces and show the results obtained...
Local invariant feature based methods have been proven to be effective in computer vision for object recognition and learning. But for an image, the number of points detected and to be matched may be very large, or even redundantly represent the shape information present. Since selective attention is a basic mechanism of the visual system, we explore whether there is a subset of salient points that...
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