Search results for "Object Detection"
showing 10 items of 64 documents
An adaptive multi-rate system for visual tracking in augmented reality applications
2016
The visual tracking of an object is a well-known problem, and it involves many fields of applications. Often a single sensor, the camera, could not provide enough information in order to track the whole object trajectory due to a low updating rate; therefore a multi-sensor system, based also on inertial measurements, could be necessary to improve the tracking accuracy. This leads to the fundamental question: how can information from different sensors be combined when they work at different rates? In this paper an approach based on recursive parameter estimation focusing on multi-rate situations is suggested. The problem is here formulated as the state-of-the-art problem of the visual tracki…
Wavelength-compensated time-sequential multiplexed color joint transform correlator
2010
We report a wavelength-compensated three-channel (RGB) joint transform correlator (JTC) for color pattern recognition using a ferroelectric liquid-crystal spatial light modulator (SLM) operating in binary pure phase modulation. We apply a previously reported time-multiplexing technique useful in creating wavelength-compensated diffraction patterns, based on the synchronization of properly scaled diffraction masks with the input wavelength selection obtained by applying a rotating RGB color-filter wheel to an Ar-Kr laser. The application of this technique to a JTC architecture permits real-time color object detection. In order to achieve a high light efficiency for the correlation process, w…
Textile and tile pattern design automatic cataloguing using detection of the plane symmetry group
2004
We present an integrated management system of pattern design for the textile and tile industries providing automatic cataloguing capabilities based on the application of the scientific theory of symmetry groups. To do this, a process of analysis is performed which starts from an initial image of the decorative element, which in turn is subjected to a number of segmentation and labelling operators that allow to detect the objects present in the image. These objects are vectorized, compared, and their isometries obtained; subsequently they are grouped and the isometries of the groups of objects detected. Finally, a composition analysis is carried out that, on the basis of the repetitions and …
Object Recognition and Modeling Using SIFT Features
2013
In this paper we present a technique for object recognition and modelling based on local image features matching. Given a complete set of views of an object the goal of our technique is the recognition of the same object in an image of a cluttered environment containing the object and an estimate of its pose. The method is based on visual modeling of objects from a multi-view representation of the object to recognize. The first step consists of creating object model, selecting a subset of the available views using SIFT descriptors to evaluate image similarity and relevance. The selected views are then assumed as the model of the object and we show that they can effectively be used to visual…
Spherical nonlinear correlations for global invariant three-dimensional object recognition
2007
We define a nonlinear filtering based on correlations on unit spheres to obtain both rotation- and scale-invariant three-dimensional (3D) object detection. Tridimensionality is expressed in terms of range images. The phase Fourier transform (PhFT) of a range image provides information about the orientations of the 3D object surfaces. When the object is sequentially rotated, the amplitudes of the different PhFTs form a unit radius sphere. On the other hand, a scale change is equivalent to a multiplication of the amplitude of the PhFT by a constant factor. The effect of both rotation and scale changes for 3D objects means a change in the intensity of the unit radius sphere. We define a 3D fil…
Temperate Fish Detection and Classification: a Deep Learning based Approach
2021
A wide range of applications in marine ecology extensively uses underwater cameras. Still, to efficiently process the vast amount of data generated, we need to develop tools that can automatically detect and recognize species captured on film. Classifying fish species from videos and images in natural environments can be challenging because of noise and variation in illumination and the surrounding habitat. In this paper, we propose a two-step deep learning approach for the detection and classification of temperate fishes without pre-filtering. The first step is to detect each single fish in an image, independent of species and sex. For this purpose, we employ the You Only Look Once (YOLO) …
Semantic Analysis of the Driving Environment in Urban Scenarios
2021
Understanding urban scenes require recognizing the semantic constituents of a scene and the complex interactions between them. In this work, we explore and provide effective representations for understanding urban scenes based on in situ perception, which can be helpful for planning and decision-making in various complex urban environments and under a variety of environmental conditions. We first present a taxonomy of deep learning methods in the area of semantic segmentation, the most studied topic in the literature for understanding urban driving scenes. The methods are categorized based on their architectural structure and further elaborated with a discussion of their advantages, possibl…
DenseYOLO: Yet Faster, Lighter and More Accurate YOLO
2020
As much as an object detector should be accurate, it should be light and fast as well. However, current object detectors tend to be either inaccurate when lightweight or very slow and heavy when accurate. Accordingly, determining tolerable tradeoff between speed and accuracy of an object detector is not a simple task. One of the object detectors that have commendable balance of speed and accuracy is YOLOv2. YOLOv2 performs detection by dividing an input image into grids and training each grid cell to predict certain number of objects. In this paper we propose a new approach to even make YOLOv2 more fast and accurate. We re-purpose YOLOv2 into a dense object detector by using fine-grained gr…
A MOBILE ROBOT FOR TRANSPORT APPLICATIONS IN HOSPITAL DOMAIN WITH SAFE HUMAN DETECTION ALGORITHM
2009
We have been developing a MKR (Muratec Keio Robot), an autonomous omni-directional mobile transfer robot system for hospital applications. This robot has a wagon truck to transfer luggage, important specimens and other materials. This study proposes a safe obstacle collision avoidance technique that includes a human detection algorithm for omni directional mobile robots that realizes a safe movement technology. The robot can distinguish people from others obstacles with human detection algorithm. The robot evades to people more safely by considering its relative position and velocity with respect to them. Some experiments in a hospital were carried out to verify the performance of the human…
Automatic object detection in point clouds based on knowledge guided algorithms
2013
The modeling of real-world scenarios through capturing 3D digital data has been proven applicable in a variety of industrial applications, ranging from security, to robotics and to fields in the medical sciences. These different scenarios, along with variable conditions, present a challenge in discovering flexible appropriate solutions. In this paper, we present a novel approach based on a human cognition model to guide processing. Our method turns traditional data-driven processing into a new strategy based on a semantic knowledge system. Robust and adaptive methods for object extraction and identification are modeled in a knowledge domain, which has been created by purely numerical strate…