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Human action recognition is a hot issue in the field of machine vision. It plays a pivotal role in human-centered computing. There are challenges mainly from the complexity of human actions and and high-noise data. Here we need to solve problems such as high intra-class variance with low inter-class variance, variable movement speed, and high computational costs. Based on the above points, we use...
3D face tracking using one monocular camera is an important topic, since it is useful in many domains such as: video surveillance system, human machine interaction, biometrics, etc. In this paper, we propose a new 3D face tracking which is robust to large head rotations. Underlying cascaded regression approach for 2D landmark detection, we build an extension in context of 3D pose tracking. To better...
Person re-identification (ReID) is an important task in video surveillance and has various applications. It is non-trivial due to complex background clutters, varying illumination conditions, and uncontrollable camera settings. Moreover, the person body misalignment caused by detectors or pose variations is sometimes too severe for feature matching across images. In this study, we propose a novel...
The ability to amplify or reduce subtle image changes over time is useful in contexts such as video editing, medical video analysis, product quality control and sports. In these contexts there is often large motion present which severely distorts current video amplification methods that magnify change linearly. In this work we propose a method to cope with large motions while still magnifying small...
This paper describes the use of Unmanned Aerial Vehicle (UAV) technology to fight apple scab. Specifically, it shows how it is possible to improve the scab risk evaluation basing on the actual apple leaves development status, yielded from UAV images, as input to the infection model. For this purpose, we introduce a new index, called Leaf Development Index (LDI), which is evaluated during the main...
Single feature of pedestrian is difficult to accurately describe the target using traditional algorithms. A new reidentification algorithm combing global features and local features with different distance metric function is introduced. First, weighted color histogram feature for whole pedestrian is extracted and combined with Bhattacharyya distance to roughly recognize targets. Then pedestrians’...
It is normally challenging to model flowering plants, which is affected by illumination, temperature, moisture, soil, etc. To further improve the accuracy and efficiency of such 3D modeling, a 3D reconstruction method for orchid flower, based on virtual binocular stereo vision, was proposed in this paper, where two cameras with baseline and fixed focal length were applied to constitute a binocular...
Coin recognition is one of the prime important activities for modern banking and currency processing systems in which machine vision is widely used. The technique at the heart of such systems is object recognition in a digital image. Although it has high recognition speed, the traditional method of coin recognition can not recognize the coins with similar sizes. This paper presents a method based...
This paper presents a computer vision-based methodology for human action recognition. First, the shape based pose features are constructed based on area ratios to identify the human silhouette in images. The proposed features are invariance to translation and scaling. Once the human body features are extracted from videos, different human actions are learned individually on the training frames of...
Fall is one of the major health challenges facing the elderly adults, especially the adults with high fall risk factors. In this paper, we aim to build a video-based model to mitigate the consequences of fall of the elderly at two application scenarios: (1) predict the fall risk caused by unbalanced gait and (2) detect a fall event as soon as it happens. In the first stage, we use a common camera...
Convolutional Neural Networks (CNNs) are responsible for major breakthroughs in object recognition in still images. This work presents an end to end very deep architecture with small convolutional kernel size, small convolutional strides and very deep network architecture for person re-identification in video streams. To achieve such system several good practices for the training were tested, namely:...
A robot needs to localize an unknown object before grasping it. When the robot only has a monocular sensor, how can it get the object pose? In this work, we present a method of localizing the 6-DOF pose of a target object using a robotic arm and a hand-mounted monocular camera. The method includes an object recognition and a localization process. The recognition process uses point features on a surface...
This paper proposed a control structure of Four-Wheel-Independent-Drive electric vehicles by motor imagery Electroencephalography (EEG) based BCI system. First work is the BCI system, Emotiv EPOC+ is used to acquire the raw EEG data, Independent Component Analysis (ICA) is used to preprocess the motor imagery EEG, then Common Spatial Pattern (CSP) is used to extract the features which is most related...
The research and application of projection interactive system based on different application scenarios has been a great development. In order to achieve natural and friendly interaction with the scene and to improve user experience, a camera-projection interactive system based on binocular vision is designed and implemented in this paper. Firstly, a foreground segmentation for moving objects is achieved...
In this paper, a visual navigation system is implemented to control a UAV in unknown and GPS-denied environments, using a monocular camera. The navigation system is based on the Semi-direct Visual Odometry algorithm, whose absolute scale is estimated by fusing visual output with altitude measurements. The main contribution of the paper is the recovery mechanisms to reinitialize the visual map when...
3D scene reconstruction from multi-view images has many practical applications, including games, virtual/augmented reality, and digital archives of cultural heritage. In this paper, we introduce a new application in video compression. The proposed idea is to have the decoder reconstruct a 3D scene model based on a subset of decoded frames and then reproject the 3D model to 2D for prediction or reconstruction...
This paper targets to bring together the research efforts on two fields that are growing actively in the past few years: multicamera person Re-Identification (ReID) and large-scale image retrieval. We demonstrate that the essentials of image retrieval and person ReID are the same, i.e., measuring the similarity between images. However, person ReID requires more discriminative and robust features to...
Periocular characteristics has gained substantial importance in recent times to supplement the performance of facial biometrics or as a stand-alone characteristics. While most of the current biometric systems for authentication or surveillance operate either in NIR spectrum or visible spectrum, the ocular information can be well utilized if a comparison of images from different spectra has to be conducted...
An autonomous navigation scheme for unmanned aerial vehicles is presented based on visual and inertial measurement information fusion without the known ground cooperative target. The UAV relative translation and rotation motion parameters are estimated by inter-frame image feature detection and tracking. Then the relative motion parameters are considered to be the relative pose measurements of two...
Person re-identification is an important technique towards automatic search of a person's presence in a surveillance video. Two fundamental problems are critical for person re-identification:feature representation and metric learning. At present, there are many methods in the study of person re-identification, which has achieved remarkable results. Due to the difference of the data distribution in...
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