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We propose a method for dietary assessment to automatically identify and locate food in a variety of images captured during controlled and natural eating events. Two concepts are combined to achieve this: a set of segmented objects can be partitioned into perceptually similar object classes based on global and local features; and perceptually similar object classes can be used to assess the accuracy...
In an aging society, a service robot will come into our life. It is important for a robot to identify an object specified by human speech from several objects. Human may request an object for the robot by its name, and/or color name etc. Although there are some research about the method for the object identification based on its name, the object identification based on its color is not discussed enough...
This paper mainly focuses on creating a global background model of a video sequence using the depth maps together with the RGB pictures. The first key concept is the near objects block the scenes at the back. With the aid of depth information, we can identify the closer moving objects. Secondly, we develop a recursive algorithm that iterates between the depth map and color pictures. Comparing to the...
Detecting and tracking a human from a mobile robot platform has several applications in service robotics where a robot is expected to assist humans. In this paper, we propose a novel interest point-based algorithm that can track a human reliably under several challenging situations like variation in illumination, pose change, scaling, camera motion and occlusion. The limitations of point-based methods...
The authors propose a novel pre-processing phase that can be integrated into conventional methods to detect and recognize planar visual objects in printed materials with low computational cost and higher accuracy. A simple yet efficient visual saliency estimation technique based on regional contrast is developed to quickly filter out low informative regions in printed materials. By eliminating noisy...
Almost every computer vision applications used background subtraction method to detect moving objects from video sequence. Moving object detection and tracking is generally the first step in many applications such as face detection, traffic surveillance, object recognition, detection of unattended bags, people counting etc. Background modeling is very useful and effective method for locating objects...
Outliers are data objects that are not highly likely to occur. These are unusualness data objects such as errors, fraud data, and rare data. In the last few decades, outlier detection has attracted much attention from researchers, because it is widely used for many different application domains. Distance-based outlier detection, which is a non-parametric approach, identifies unusual data objects in...
In this paper, an efficient and automatic method for detection of multiple-objects of interest from images is presented. This method is based on using region similarity measures. The method starts by constructing two knowledge databases in which significant and distinctive textures extracted from both objects of interest and background are respectively represented. The proposed procedure continues...
Much research has been done to block objectionable images by analyzing the visual contents. The region-of-interest based approach are more accurate in describing the image content than the approach using the whole image in the field of content-based image retrieval. Therefore, this paper proposes a method for classifying objectionable images based on global features and salient region. By using the...
In this paper, we propose LinedCut: a novel method for interactive image segmentation which requires only a single line drawing to identify the object of interest in the image. The handy interaction mode can address the problem of object scale very well. Our approach consists of the following three steps: first, a given image is over-segmented into superpixels using superpixel algorithm; secondly,...
In this paper, robot control by human motion data is considered. The conventional motion reproduction structure had its limitation on the performance due to the lack of means for environmental sensing. This study implements the widely used vision based approach. The possible reproduction structure with both visual and tactile senses are discussed. The proposed reproduction structure with both visual...
We are developing a helper robot able to fetch objects requested by users. This robot tries to recognize objects through verbal interaction with the user concerning the objects that it cannot detect autonomously. We have shown that the system can recognize objects based on an ontology for interaction. In this paper, we extend a human description ontology to link a "human description" to...
For the need of actually combining RGB data and depth input in computer vision research, new RGB-D features for object recognition are proposed. We present six kinds of RGB-D kernel matching functions on kernel view. They have the capability of capturing different RGB-depth cues including position, size, shape and distance. Due to the infinite dimensional character in Gaussian space, it is computationally...
Analysis and recognition of objects in complex scenes is a demanding task for a computer. There is a selection mechanism, named visual attention, that optimizes the visual system, in which only the important parts of the scene are considered at a time. In this work, an object-based visual attention model with both bottom-up and top-down modulation is applied to the humanoid robot NAO to allow a new...
We learn to direct visual saliency in multimodal (i.e., pointing gestures and spoken references) human-robot interaction to highlight and segment arbitrary referent objects. For this purpose, we train a conditional random field to integrate features that reflect low-level visual saliency, the likelihood of salient objects, the probability that a given pixel is pointed at, and - if available - spoken...
In a physicalist theory of mind, a concept is a mental representation, which the brain uses to denote a class of things in the world. They can help us classify newly encountered objects on the basis of our past experiences. But how can we get the concepts? As visual information account for about 80% of total perceptual information, this paper proposes a concept acquisition method based on visual cognition...
The approach developed in this paper is about objects recognition. The method consists to recognize objects that are partially occulted. A modified alignment approach is also considered to make our approach invariant to rotation. The proposed technique consists to create first, an index containing codes associated to each image of the database. The index is created using two techniques; the Quad-tree...
Color feature and its measurement are important foundations and means in evaluating product quality and are widely used in the food, pharmaceutical, industry and agriculture fields. The paper implements the identification of heterochrome objects in particle materials based on color feature. According to color model classification from the view of application, it selects RGB color model and HSI color...
This paper focuses on the object recognition task and aims at improving the accuracy with an emphasis on the feature extraction step. Feature extraction is widely used in image classification as an initial step in the pipeline. In this paper, we propose a method to explore the conventional feature extraction techniques from the perspective that mid-level information could be incorporated in order...
Object discovery is the task of detecting unknown objects in images. The task is of large interest in many fields of machine vision, ranging from the automatic analysis of web images to interpreting data of a mobile robot or a driver assistant system. Here, we present a new approach for object discovery, based on findings of the human visual system. Proto-objects are detected with a segmentation module,...
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