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Scene analysis is very important in a video surveillance system, with purpose to gain information and knowledge from the surrounding. There are many researches covering problems in object detection and tracking, but solve it only partially. This paper will cover an integral technique to do object detection and tracking for video surveillance. First, pixels in the images will be modelled with gaussian...
In this paper, we propose an approach for achieving generalized segmentation of microorganisms in microscopy images. It employs a pixel-wise classification strategy based on local features. Multilayer perceptrons are utilized for classification of the local features and is trained for each specific segmentation problem using supervised learning. This approach was tested on five different segmentation...
With the increasing proportion of senior citizens, many mobility aid devices have been developed such as the rollator. However, under some circumstances, the latter may cause accidents. The EyeWalker project aims to develop a small and autonomous device for rollators to help elderly people, especially those with some degree of visual impairment, avoiding common dangers like obstacles and hazardous...
The ability to detect and localize an object of interest from a captured image containing a cluttered background is an essential function for an autonomous robot operating in an unconstrained environment. In this paper, we present a novel approach to refining the pose estimate of an object and directly labelling its contours by dense local feature matching. We perform this task using a new image descriptor...
Although substantial progress has been made in objects detecting in point clouds, the performance of most methods is limited by the accuracy of segmentation. However, accurate segmentation in complex scene is still an open problem. This paper presents a novel rotation-invariant method for object detection. It uses Adaboost to train a detector for exhaustively scaning and testing of the point cloud...
Finding an object in a 3D scene is an important problem in the robotics, especially in assistive systems for visually impaired people. In most systems, the first and most important step is how to detect an object in a complex environment. In this paper, we propose a method for finding an object using geometrical constraints on depth images from a Kinect. The main advantage of the approach is it is...
We investigated effective features for human detection. The histogram of oriented gradients (HOG), which was proposed by N. Dalal, is an important representation that accumulates the edge-magnitude into a quantized histogram. Effective features similar to the HOG have been proposed. We question what the most effective feature is. We thus evaluate several features on three datasets of pedestrians,...
In this paper, an algorithm of target region detection is proposed based on superpixel segmentation in the field of computer vision which is imported to high-resolution remote sensing images for superpixel-level rather than pixel-level target detection. For the problem of massive data, redundant information and time-consuming targets searching of high-resolution remote sensing images with complex...
Most existing approaches to detecting semantic objects in a video use an object detector to locate the target object in the first frame, which is followed by an object tracking to locate objects in successive frames. However, automatic modeling, tracking and detecting semantic-rigid objects remain a challenge since the object shapes are deformable across video frames. This paper presents an analytical...
In the paper, we consider the probability of applying hyper-spectral image (HSI) processing methods to panchromatic images (PIs), which is a novel yet crucial issue for further analyses. To achieve the purpose, we propose an effective approach for handling PI with HSI unmixing methods. In the approach, HSI simulating process is first implemented to obtain a synthetic HSI from PI. After that, a hyperspectral...
This paper describes a novel approach for generating object proposals for ball detection. Our method, called shape detector, captures the possible contours of balls and then transfers them into proposal bounding boxes which may contain the target object. These proposal bounding boxes can be further used in class-specific object detection task. Our experiment results on part of ILSVRC dataset show...
In this paper, we propose a novel object detection algorithm for underwater environments exploiting multiscale graph-based segmentation. The graph-based approach to image segmentation is fairly independent from distortion, color alteration and other peculiar effects arising with light propagation in water medium. The algorithm is executed at different scales in order to capture both the contour and...
This paper proposes a promising new approach to detect underwater threats in side scan sonar (SSS) images without machine learning procedure. Although object detection requires high reliability, the maritime environment changes unpredictably and dynamically. In order to accomplish high reliability for object detection systems, a huge number of the samples under various different environments are required...
Object recognition is a very important task in computer vision and different techniques have been presented to solve it. In this paper a Hough-type low-computational algorithm for detection of objects in cluttered scenes is presented. The approach is based on the detection of the shape of an object, modeled by means of a set of corners. An automatically model learning method is introduced. The method...
This paper presents a new and efficient approach for automatic pedestrian detection in infrared images. The approach consists of three steps; initially, background subtraction model designed based on the input image intensity properties of target and background region to suppress the noise in image. Secondly, order statistics filter is applied on the background suppressed image to enhance the target...
Exhibition content has been used a touch panel for the user's convenience. Touch panel are not good recognition. And errors may occur when you use a long time. In addition there occurs a malfunction due to contamination. In the present study, such problems want to improve. We designed the Exhibition contents to recognize the swipe gesture of Kinect. Gesture recognition is constructed in three steps...
This paper proposes an innovative method to detect micro aerial vehicles (MAVs) and estimate their relative pose in formation using a monocular on-board camera. Haar classifier is trained for autonomously detecting MAV in open scenes, like grasslands or obstruct-free playgrounds. In order to increase the robustness of the detection, a Kaiman filter has been employed to conduct image tracking. Contours...
This study presents a method for detecting an object by using several features. Features are extracted based on the statistical distribution of points on the bitmap image of the shape. It detect the shape of an image by using geometrical features and then select the clustered of image that matched that shape from a large database. In this approach the image of object are divided into zones and find...
This paper presents the detection and localization methods of entrance and staircase markers for the team E-Mobile in TechX Challenge 2013. Autonomous vehicles are required to detect and locate traffic cones beside the indoor entrance and staircase. One big challenge is from the unpredictable lighting conditions and environment. Different practical techniques such as color space selection, segmentation,...
Image processing techniques play an important role in military applications. Image binarization could be understood as a process of pixel values segmentation of grayscale image into two value groups, zero as a background and 1 as a foreground. In simple humorapplication of object detection we assume that contrast distribution of foreground is uniformed and without background noise or that variation...
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