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This article develops a geometric framework for detecting targets, in the form of regions of interest, from certain sonar imagery. The main idea is to extract level sets from voxel images and compute local geometric features of the resulting surfaces. Examples include Gaussian and principal curvatures, radial distances, patch areas etc. These features are then compressed into histograms, or estimated...
We present hierarchical multi-feature classification (HMC) system for multiclass fruit recognition problem. Our approach to HMC exploits the advantages of combining multimodal features and the fruit hierarchy property. In the construction of hybrid features, we take the advantage of using color feature in the fruit recognition problem and combine it with 3D shape feature of depth channel of RGBD (Red,...
Most objects are designed for certain functionalities. For example, a knife is designed for cutting, and a hammer for pounding. Indeed, functionalities are not related to the objects themselves but to certain object parts, e.g., the blade of a knife affords cutting. A part can have different shapes and can exist in different objects such as a scraper or a peeler, but it carries the same functional...
Video surveillance system is widely adopted in order to secure life. This paper presents embedded home surveillance systems to detect intruder in home environment. Proposed system works on embedded Linux board which is equipped with an ordinary web camera. At software level, it uses Open Computer Vision library to detect intruder in two different steps, Histogram of Oriented Gradient and Haar Like...
The work is devoted to the problem of weld segmentation in modern methods for evaluating the quality of welds. One of the methods of the weld quality evaluation is visual inspection. This work deals with the possibility of implementing algorithms of recognition and evaluation of welds using visual system in single-board computers. Result of this paper is computing time comparison of chosen embedded...
3D Object recognition is one of the big problems in Computer Vision which has a direct impact in Robotics. There have been great advances in the last decade thanks to point cloud descriptors. These descriptors do very well at recognizing object instances in a wide variety of situations. Of great interest is also to know how descriptors perform in object classification tasks. With that idea in mind,...
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...
Pedestrian detection and counting is an important topic in developing an intelligent surveillance system. In this work, we propose a vision-based system for detecting pedestrians in an image. Be robust to crowded scenes and adapt to incomplete foreground from background subtraction algorithm, expectation maximization (EM) algorithm is applied to impose the constraint of body part for achieving successful...
Human action recognition has been one of the most challenging topics in computer vision during the last decade. This paper presents a novel approach for recognizing view independent human actions based on analysis of Fourier transform and Radon transform of self similarity matrix of features obtained from the action. The proposed feature descriptor is extracted from human point cloud over the time...
To understand the human action in still images, it is effective to detect the human region. However, since appearance of human is much different due to pose and occlusion, the detection is quite difficult. Here we propose robust human detection method to pose and occlusion using Bag-of-Words (BoW). In general, the location information is helpful in classification. When the human has occlusion and...
Shape context is a classic shape retrieval method with translation invariance, but it has not scalar or rotational invariance, which limits its application. A new shape feature descriptor-centroid distance ratio (CdR) is proposed and an improved shape retrieval algorithm based on CdR and shape context is brought forth. First, the contour points are sampled in order to reduce computation and then,...
Mobility in large touristic cities (such as Rome and Venice), where needs of citizen and tourists are different(and sometimes even conflicting), is a very relevant problem and info mobility is thus increasingly important. Since active technologies, requiring the passengers to wear some devices(e.g., RFID devices) are not commonly available and cannot be enforced on citizens and tourists, a complete...
With the proliferation of digital cameras and automatic acquisition systems, scientists can acquire vast numbers of images for quantitative analysis. However, much image analysis is conducted manually, which is both time consuming and prone to error. As a result, valuable scientific data from many domains sit dormant in image libraries awaiting annotation. This work addresses one such domain: coral...
Human action recognition and interpretation constitutes an important part of the video understanding. In this work, a novel action recognition system is developed that uses edge features obtained from optical flow power shapes which is represented as sequential gradient histograms. The presented system can achieve equal results to the complicated top action recognition systems of nowadays. The system...
In the field of computer vision, pyramid matching by minimization has gained increasing popularity. This paper points out and discusses an inherent anomaly in pyramid matching by minimization that can affect the performance of classification approaches based on this type of matching. As a solution, a new multiresolution measure, called Manhattan-Pyramid Distance (MPD), is proposed. Systematic evaluations...
Nowadays leaf image classification is very useful for both botanists and ordinary users since advanced imaging devices such as smart phones make it ever easier to capture leaf images for various tasks such as retrieval and classification. Most of existing approaches mainly utilize global shape features. In this paper, we propose to improve leaf image classification by taking both global features and...
This paper presents an efficient approach to detecting upper body in unconstrained posture based on Shape Context and Histograms of Orient Gradients. The method contains two steps. Shape context matching is used to get the candidates of upper bodies in the images at first, and then validation of each candidate is performed by using the Histograms of Orient Gradients. The method has two advantages,...
The structure from Motion (SfM) algorithm is an established method of shape recovery from a single video sequence. However, limitation of the method is the accuracy of the recovery due to poor texture of a recovered plane or a large scale object. We propose a technique for improving the precision of the recovery by applying the Manhattan-world constraint to the SfM algorithm, which assumes that the...
In this paper, we present a non-symmetry and anti-packing object pattern representation model (NAM) for object detection. A set of distinctive sub-patterns (object parts) is constructed from a set of sample images of the object class; object pattern are then represented using sub-patterns, together with spatial relations observed among the sub-patterns. Many feature descriptors can be used to describe...
This paper presents a method for representing and recognizing human actions based on pose similarity. For pose representation, we extend Histogram of Oriented Gradients (HOG) with directional statistics to obtain a HOG based descriptor with a smaller dimension. Then a directional similarity measurement for the proposed descriptor is put forward to provide a measure consistent with human perception...
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