The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
We propose a novel approach for multi-view object detection in 3D scenes reconstructed from RGB-D sensor. We utilize shape based representation using local shape context descriptors along with the voting strategy which is supported by unsupervised object proposals generated from 3D point cloud data. Our algorithm starts with a single-view object detection where object proposals generated in 3D space...
Commonly, HoG/SVM classifier uses rectangular images for HoG feature descriptor extraction and training. This means significant additional work has to be done to process irrelevant pixels belonging to the background surrounding the object of interest. While some objects may indeed be square or rectangular, most of objects are not easily representable by simple geometric shapes. In Bitmap-HoG approach...
ShapeNets is an image representation, which is based on shape, compact structure, hierarchical image structure and appearance characteristic of object contour. In a ShapeNets, the shape of image is a window of containing objects which can be extracted with the method of objectness. The outline of objects can also be extracted in a line boundary detection algorithm based on histogram of gradients direction,...
The paper discusses the passive optical detection of small-sized targets moving through the air at overhead levels. An experimental module for a standalone locator to operate in real time is presented together with methods usable within the actual implementation of the underlying designer project. Within the supporting tests, an algorithm was developed to detect small particles in a video sequence,...
Research about determining infertility rate of sperm is still being under constant development. First important phase on the sperm infertility observation is detection of sperm object. Success rate of separate sperm with semen fluids has important role for further analytical measure. This research is on its ways to detect and count human's spermatozoa. Detected sperms are moving sperm that is moving...
This paper presents efficient object tracking in video sequences using multiple features by embedding mean shift into particle filters. When clutter background and occlusions are present. Particle filtering is used because it is very robust and performs well for non-linear and non-Gaussian dynamic state estimation problems. The image features, such as shape, texture, color, contours, and random motion...
Travelers, sailors and research people working in sea environment are facing lot of challenges. One such challenge is salt water crocodile. In general, crocodiles are seen in fresh water like lake and river. Nowadays it is migrated to salt water. These salt water crocodiles are serious threat to travelers and sailors. This issue is addressed through solution like Ocean Observation System (OOS), which...
In video surveillance, moving object detection has become one of the core techniques to understand video content. Many detection methods exist to detect objects, but cannot effectively compensate for the effect of shadows or incomplete shapes of moving objects. In this paper, we apply image bit-planes and hysteresis thresholding to compensate for the loss of spatial and temporal information. The experimental...
Production of Ground Truth (GT) data for remotely sensed images is an important step for evaluation of accuracy assessment of different analyzes such as classification, geo-locatining and object detection. Geo-locationing systems for images taken from different platforms such as ground and laboratory tripod are not widespread and useful. Lack of peer pixel coordinates of image pixels is an absence...
In this simulation study, the proposed Inshore object detection model has been investigated to detect the objects in the oceanic images in order to reduce the human effort to shortlist the images containing the useful information. The simulative analysis focus on the design and implementation to use the hybrid combination of the color and shape based analysis to detect the objects precisely. The MATLAB...
This paper describes approach to detect object using its shape and color information which is capable of detecting object rapidly and comparatively with good detection rate. This work divided into two part. First how to use color information to segment the object and secondly how to compare the contour of extracted object with contour of object to be the detected. Proposed method uses Fourier descriptor...
Image and video processing is a very important topic for research in the world. Its application pervade in the whole world, as perceived in video surveillance, anomaly detection, human action analysis etc. Nevertheless some drawbacks are there, as there is large storage required for storing the data and retrieval of a particular data and from the colossal storage it is very difficult or in some case...
Many of object detection methods are based on training phase. Theses methods are constrained to a known object. In this paper, we present a free training method for object detection that can deal with large viewpoint change. We exploit Dempster theory to combine between multiple descriptors in a multi stage method. To show the effectiveness of the technique, we apply it on multiple images from Coil100...
Detection and segmentation are two strongly correlated tasks, yet typically solved separately with different techniques for repetitive patterns or simultaneously solved for generic patterns. We propose a Simultaneous Detection and Segmentation model for Repetitive pattern analysis (SimDSR) in real-world images. The proposed SimDSR model implements a joint patch-contour alignment between the multi-scale...
Detection of an object and tracking its movement is a challenging problem in the field of computer vision and image processing. In this paper an efficient scheme has been proposed to detect intrusion in a security-critical environment and to track the movement of the intrusion by automatically shifting the focus of a CCTV camera by rotating it using a motor which has been interfaced through an Arduino...
The oceanography is the technnique of analyzing the oceanic imagery in order to find the useful information about ships, objects. The technique is helpful in detecting the lost ships, boats, aero planes, debris, containers, etc. It may consists of the large volumes of image data, which must be further shortened to find the useful information to find the lost objects in the oceanic area. In this simulation...
In this paper, an approach for matching of primitive shapes detected from point clouds, to boundary representations of primitive shapes contained in CAD models of objects/workpieces is presented. The primary target application is object detection and pose estimation from noisy RGBD sensor data. This approach can also be used to determine incomplete object poses, including those of symmetrical objects...
The automated detection of abandoned objects is a quickly developing and widely researched field in video processing with specific application to automated surveillance. In the recent years, a number of approaches have been proposed to automatically detect abandoned objects. However, these techniques require prior knowledge of certain properties of the object such as its shape and color, to classify...
Object detection from images is generally achieved through a supervised learning manner. However, in many real applications, to provide instance level label is still costly. Thus, weakly supervised approach is proposed and naturally cast as a Multiple Instance Learning (MIL) problem. Traditional MIL methods typically learn discriminative classifiers from positive and negative training bags. Alternatively,...
Recently robots working in various situations as workplace and nursing home autonomously are expected. In those situations, it is important for such robots to recognize surrounding environment and to avoid the risk to people. We propose a method to realize an autonomous robot moving smoothly and safely with low calculation cost by performing motion prediction and human detection in dynamic or static...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.