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Re-identification refers to the task of finding the same subject across a network of surveillance cameras. This task must deal with appearance changes caused by variations in illumination, a person's pose, camera viewing angle and background clutter. State-of-the-art approaches usually focus either on feature modeling — designing image descriptors that are robust to changes in imaging conditions,...
In this paper we would describe a vehicle detection technique that can be used for traffic surveillance systems. An intelligent traffic surveillance system, equipped with electronic devices, works by communicating with moving vehicles about traffic conditions, monitor rules and regulations and avoid collision between cars. Therefore the first step in this process is the detection of cars. The system...
In this paper, we propose a new method that can reconstruct the more accurate 3D surface point clouds from the standard laparoscopic (single camera) imaging system even with less sequential (less overlapped) and low quality images, which is a promising way to achieve a faster surgical guidance. The strength of our method is to find more accurate feature points that lead to precise 3D reconstruction...
With the rapid increasing of railway mileage, automatic railway intrusion detection by analyzing the video from train-mounted camera is becoming very meaningful. But there exits serious jitter in the video since the camera always vibrates with train when it is running, a video stabilization reprocessing procedure is the prerequisite before the intrusion detection analysis. To solve this question,...
Person re-identification is one of the widely studied research topic in the fields of computer vision and pattern recognition. In this paper, we present a deep multi-instance learning approach for person re-identification. Since most publicly available databases for pedestrian re-identification are not enough big, over-fitting problems occur in deep learning architectures. To tackle this problem,...
Activity recognition from first-person (ego-centric) videos has recently gained attention due to the increasing ubiquity of the wearable cameras. There has been a surge of efforts adapting existing feature descriptors and designing new descriptors for the first-person videos. An effective activity recognition system requires selection and use of complementary features and appropriate kernels for each...
We address the problem of people detection in top-view fisheye imaging. Even within the same top-view fisheye frame, upright people appear slanted in various directions and are distorted in different ways. Due to this variability, standard people detectors are not directly applicable to top-view fisheye frames, and dedicated people detectors for the top-view fisheye domain are hard to design. We extract...
The vibration response of a damaged bridge is known to have changed characteristics. To analyze the response, we start by collecting waveforms of the vibration immediately following the passage of a vehicle. We then need to isolate just those vibrations caused by a single heavy vehicle, if the vibration characteristics are to be accurate. In this paper, we propose a traffic-vibration analysis system...
The tracking and labeling of multiple objects in multiple cameras is a fundamental task in applications such as video surveillance, autonomous driving, and sports analysis. In an ad-hoc multi-camera network without a fusion center nodes can benefit from local cooperation to solve signal processing tasks, such as distributed image enhancement. A crucial first step for the successful cooperation of...
Person re-identification (ReID) stands for the task of determining the co-occurrence of individuals across a network of cameras with disjoint viewfields. The relevant literature documents a plausible number of contributions so far. KISS metric learning is an effective ReID method. However, as reported in the existing works, KISS metric learning is sensitive to the feature dimensionality and can not...
Low resolution commercial 3D sensors contribute to computer vision tasks even better when the analysis is carried out in a combination with higher resolution image data. This requires registration of 2D images to unorganized 3D point clouds. In this paper we present a framework for 2D-3D data fusion to obtain directly the camera pose of a 2D color image in relation to a 3D point cloud. It includes...
In this paper we propose a gait pattern analysis system that uses stereo vision and machine learning techniques for robotic walker applications. This work contributes with a user monitoring system, that allows the development of more user-centered approaches, such as safer and adaptive HMIs. It also provides a tool to help healthcare personnel in medical assessments. The gait analysis system presented...
Affective facial expression is a key feature of nonverbal behaviour and is considered as a symptom of an internal emotional state. Emotion recognition plays an important role in social communication: human-to-human and also for human-to-robot. Taking this as inspiration, this work aims at the development of a framework able to recognise human emotions through facial expression for human-robot interaction...
This research proposes the use of Harris Corner Detector and Lucas-Kanade Tracker methods for the detection of 3D objects based on stereo image. The test image obtained from the results of capturing of the camera to the object of the form of tubes, balls, cubes, and 2D images. This research is the early step in the development of the ability of a computer vision to be able to mimic the performance...
In the animation movie production, there is a common tool namely motion capture (mocap) to capture the motion of actors. Using this technology, reconstruction of actors motion is being mapped to drive 3D character in the animation. In the reconstruction process of human motion, there were some significant parameters that affect the quality of the result such as subtle motion and high precision reconstruction...
This paper focuses on a novel approach for handling radical overhaul of anomalous behavior in a visual surveillance network. The initial objective is online detection of anomalies using a Kernel-based online anomaly detection algorithm. The algorithm will operate onimages collected from a moving camera over a span of space and time. The proposed algorithm established based upon machine learning principles...
In this paper a new pupil detection algorithm based on RANSAC procedure is presented. Unlike other similar algorithms reported in the literature, the proposed algorithm provides higher accuracy, low running time and operates properly in noise conditions and for variable illumination. This algorithm is used in the field of assistive technology in order to communicate with neuromotor disabled people...
To quickly and efficiently analyze a large-scale environment by the camera with limited field-of-view, intelligent systems should sequentially select the optimal field-of-view to observe important and informative parts of area. Especially in the image retrieval tasks, small observations could be sequentially selected to improve the performance of image retrieval with less computational costs than...
This paper describes a method of grasp point detection from an item of cloth with unarranged shape. We focus on the combination of grasp point detector with shape classifier. In the proposed method, Convolutional Neural Network(CNN) is generated for shape classification, and it is also used for extracting a feature vector that presents shape characteristics. Using the feature, grasp points are calculated...
In a smart city build-up, intelligent transportation system (ITS) is essential for efficient and adaptive control of the transportation system. In order to have a meaningful ITS, availability of statistics such as types of the objects (vehicles, human, etc.) in motion and their statistics and interaction with the environment, are important. Automatic classification of moving objects is an important...
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