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Challenging ground truth and standardized metrics are a mandatory requirement for the development and evaluation of computer vision algorithms. Despite the significant amount of publications on video based fire detection research it remains difficult to compare different algorithms due to the lack of common evaluation schemes and evaluation datasets. We address both of these issues by presenting a...
Human-autonomy sensor fusion is an emerging technology with a wide range of applications, including object detection/recognition, surveillance, collaborative control, and prosthetics. For object detection, humans and computer-vision-based systems employ different strategies to locate targets, likely providing complementary information. However, little effort has been made in combining the outputs...
The aim of this paper is to present the algorithms that were developed for detecting human in the conditions of overlapping and non-overlapping. Overlapping means when person is not fully visible in the image and occluded by another person at the front or right/left side. In order to achieve this goal, three steps were implemented. The algorithms were implemented in C++ with the help of Open Source...
Humans have the natural capabilities to perceive and anticipate actions of objects they interact with, including incidents happen within their neighborhood. These days, this important aspect of human perception has been widely incorporated in the computer vision framework to perform human action detection task. However, little attention is paid to the problem of detecting ongoing human actions as...
In this paper, we present a method for joint tracking of individuals and groups in surveillance scenarios. Groups are dynamic entities and they may grow or shrink with merge-split events. This dynamic nature makes it difficult to track groups using conventional trackers. In this paper, we propose a new tracking method named Conjoint Individual and Group Tracker (CIGT) based on particle filter with...
In this paper, a Binary Robust Invariant Scalable Keypoints (BRISK) based detection is utilized to facilitate the flying unmanned aerial vehicle (UAV) localization within its autonomous landing on the runway. Specifically, two target detection algorithms are proposed and developed as the BRISK-supported approach. Dataset of images and differential GPS are recorded by a ground stereo vision guidance...
Color represents an important attribute in the field of traffic sign recognition. However, when the color of the traffic sign fades or the traffic scene is collected in gray as in the case of Infrared imaging, then color based recognition systems fail. Other problems related to color are simply that different countries use different colors. Even within the European Union, colors of traffic signs are...
Object-based scene image representations can effectively capture the semantic meanings of a scene. However, they usually neglect a scene's structure information. In this paper, we propose a novel and effective detector-based scene representation method for scene classification. In particular, we extract object features by object detectors. By sensible principal component analysis, we obtain a compact...
In this paper we propose an efficient approach for circular shape target recovery. The method makes use of the conterminous set of edge segments, or contour segments, instead of the huge edge points as traditional detectors do. First, the proposed approach computes the contour in a given image, which is then converted into contour segments at high curvature points. Then, by calculating the reinforcement...
Despite the wide applications of matching descriptors, much work hasn't been done on it. In the current paper, we extended the use of the existing techniques in object detection in 2D images to video sequences by extracting the Spatio-temporal Interest points using spatio-temporal Harris detector. Features descriptors are computed on the pixels around these interest points. To match between descriptors,...
In this paper we describe a new dataset, under construction, acquired inside the National Museum of Bargello in Florence. It was recorded with three IP cameras at a resolution of 1280 × 800 pixels and an average framerate of five frames per second. Sequences were recorded following two scenarios. The first scenario consists of visitors watching different artworks (individuals), while the second one...
Our paper proposes a novel method for fire detection in riot videos acquired with handheld cameras and smart-phones. This is a typical example of computer vision in the wild, where we have no control over the data acquisition process, and the quality of the video data varies considerably. We propose a novel spatial model for fire, based on Gaussian mixtures and on color adjacency in the visible spectrum...
The detection of play and break segments in team sports is an essential step towards the automation of live game capture and broadcast. This paper presents a two-stage hierarchical method for play-break detection in non-edited video feeds of sport events. Unlike most existing methods, this algorithm performs action and event recognition on content, and thus does not rely on production cues of broadcast...
In this paper we propose a hybrid feature-based wallpaper visual search system. As opposed to conventional techniques that use global features to perform wallpaper search, this paper proposes to integrate local and global features to support both functions of recognition (identify the product ID of the query images) and retrieval (search wallpapers that are visually similar to the query images). An...
There has been an increased interest in the field of abnormal human activity detection to find a good descriptor with a lower computational cost. In this paper, we propose such a Spatio-Temporal Descriptor (STD) based on spatio-temporal features of an image sequence. Proposed descriptor is based on a texture map, known as Spatio-Temporal Texture Map (STTM) and is based on 3-dimensional Harris function...
Different methods employed for object detection are widely exploited covering application areas such as traffic monitoring, video surveillance and capturing various human activities and motion. The traditional methods that have earlier been proposed for detection are found to be beneficial if the detected object is properly identified. Moreover, minimizing the effect of dynamic changes as well as...
If we compare the object recognition abilities of human and computer-based system, it is much complex task for a machine. Human brain can recognize an object quickly but for a computer system accuracy depends on the level of algorithms, software and tools used for recognition. Image processing, pattern recognition and compute vision are being challenging but becomes a crucial component for developing...
Tracking unknown objects using adaptive tracking-by-detection approaches are widely used in computer vision. In these approaches, tracking problem is treated as an online classification problem, where the object classifier model is updated in the current frame to be used for classification process in the next frame. One of the approaches is based on Tracking-Learning-Detection (TLD) framework, where...
Corners are important image features whose detection is very important in many computer vision tasks. In this paper we have evaluated the performance of five intensity based corner detectors with the help of a dozen test images, artificial and real, based on six performance measures of which three are proposed by us. We then propose a new approach, using bitplane decomposition, in which a grayscale...
Face detection is widely used in interactive user interfaces and plays a very important role in the field of computer vision. In order to build a fully automated system that can analyze the information in face image, there is a need for robust and efficient face detection algorithms. One of the fastest and most successful approaches in this field is to use Haar-like features for facial appearance...
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