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This paper presents a general framework for live detection of broilers in poultry houses. The challenges for image recognition of broilers are posted by crowded scenes, poor image quality and difficulty in acquiring a benchmark of labeled samples. The proposed framework consists on the use of image thresholding, morphological transformations, feature engineering, in addition to supervised and unsupervised...
A first-person camera, placed at a person's head, captures, which objects are important to the camera wearer. Most prior methods for this task learn to detect such important objects from the manually labeled first-person data in a supervised fashion. However, important objects are strongly related to the camera wearer's internal state such as his intentions and attention, and thus, only the person...
Object detection and classification are two very important tasks for quality control in industrial process. The first step of a quality algorithm is the detection of the moving object. Afterwards, the detected object is classified according to its size and color related properties. In this study, an interactive image segmentation method is proposed to detect a moving object. The segmentation method...
An approach for object detection in depth images based on local and global convexity is presented. The approach consists of three steps: image segmentation into planar patches, greedy planar patch aggregation based on local convexity and segment grouping based on global convexity. The proposed approach improves upon existing similar methods, which use convexity as a cue for object detection, by detecting...
Capturing image with defocused background by using a large aperture is a widely used technique in digital single-lens reflex (DSLR) camera photography. It is also desired to provide this function to smart phones. In this paper, a new algorithm is proposed to synthesize such an effect for a single portrait image. The foreground portrait is detected using a face prior based salient object detection...
We introduce a new large-scale data set of video URLs with densely-sampled object bounding box annotations called YouTube-BoundingBoxes (YT-BB). The data set consists of approximately 380,000 video segments about 19s long, automatically selected to feature objects in natural settings without editing or post-processing, with a recording quality often akin to that of a hand-held cell phone camera. The...
The paper proposes an intelligent K-means segmentation algorithm that clearly segments foreground objects and completely occluded objects. When a person completely occludes an object while entering into the area of video surveillance, it is considered as an anomaly. The paper comes up with a robust technical solution to address this. The proposed algorithm chooses an optimal value for K and segments...
In this paper, we propose an improved fuzzy enhancement algorithm for the moving object detection and tracking. A new membership function is proposed based on the theory of fuzzy sets, which improves the traditional Pal-King fuzzy enhancement algorithm and overcomes the loss of gray information after the processing of enhancement. Since a gray image with multiple targets need more than one crossover...
The problems of object detection on an image and labeling of pixels, corresponding to each detected object (segmentation) are solved. In the work we have examined such issues as filtering and preparation depth data, extraction of semantically rich features vectors from the RGB-D images and classification methods, allowing implementing the objects detection and segmentation.
Reconstructions of outdoor and indoor environments using stereo cameras are confronted with harmful effects caused by moving objects. Ghosting shown in Fig.1 not only leads to misunderstanding but also hamper the reconstruction of the static scene. 3D map with only still objects can be used for robotics navigation after moving-object detection. Nevertheless, blanks maybe occurred in the 3D map once...
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,...
Object detection is a hot spot of the research in computer vision since many applications require the determination of the object location. There are many object detection methods based on feature matching methods. In this paper, we locate object on robot operation system. The SIFT keypoints of the template and test images are extracted at first. Then, the matching method is proposed to find the template...
In this paper, a vision tracking system via color detection is presented. In this system, a monocular camera is used as a sensor to track and measure the relative pose of the target based on specified color detection with the help of four LED markers. Kalman filter is used in this system to predict the position of LED markers in the next frame of the camera image so as to decrease the area in which...
The objective of paper is to review the video segmentation and moving object detection methods, organize them into different categories. Object detection and tracking is a stimulating problem. The object identification can identify a moving object and discard unwanted candidate area which does not include an interesting object. The techniques used for the general video segmentation for traffic surveillance...
Pervasive computing applications have long used contact free object detection to process images collected from smartphone, tablet and wearable cameras. Two key challenges encountered in uncontrolled environments are the detection accuracy and speed, more so on computationally limited embedded systems. Recent technological advances have led to the emergence of depth sensors being integrated in a variety...
Monitoring marine object is important for understanding the marine ecosystem and evaluating impacts on different environmental changes. One prerequisite of monitoring is to identify targets of interest. Traditionally, the target objects are recognized by trained scientists through towed nets and human observation, which cause much cost and risk to operators and creatures. In comparison, a noninvasive...
The paper presents the application of graph-based segmentation algorithm in image object detection. The input images are taken from thermal camera for night surveillance application. The graph-based algorithm was selected due to its low complexity, which allows us to process each image with the complexity of O(n.log(n)) where n is the number of pixels, and due to the fact that thermal images contains...
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...
We present a street scene layout estimation method based on transferring layout annotation from a (large) image database and its application for distant object detection. Inspired by nonparametric scene labeling approaches, we estimate a scene's geometric layout by matching global image descriptors and retrieving the most similar layout configuration. Our label transfer is done for each sub-region...
CubeSats are standardized artificial nano satellites which weigh between 1 and 15kg and serve the purpose of space research. A handful of cubesats have proved their worth to the world with their payloads based on terrestrial monitoring. The so-called remote sensing cubesats have revolutionized the platform for different scientific observations that include weather forecast, cyclone warning systems,...
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