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In Convolutional Neural Network (CNN)-based object detection methods, region proposal becomes a bottleneck when objects exhibit significant scale variation, occlusion or truncation. In addition, these methods mainly focus on 2D object detection and cannot estimate detailed properties of objects. In this paper, we propose subcategory-aware CNNs for object detection. We introduce a novel region proposal...
This paper presents 3D model generation of cattle by shape-from-silhouette method for ICT agriculture. The use of advanced ICT has any possibility to improve various agricultural activities. The authors have such a project whose targets are beef cattle. The goal of the project is to capture 3D shape information of cattle for the estimation of their body condition scores (BCS). Cattle do not stop moving...
Stereo cameras are widely used in autonomous vehicles as environmental perception sensors because of their availability and low cost. However, efficiently utilizing the obtained disparity images to generate a desirable local path for the vehicle still remains a challenging problem. In this paper, we present a novel navigation framework for autonomous vehicles equipped with stereo cameras, featuring...
In this work, we propose an integration of the LiDAR device and a pair of binocular cameras for egomotion estimation and 3D reconstruction. The proposed system simultaneously acquires both range data and image data as input and calibrates the LiDAR and the cameras to determine the correspondences between them. Egomotion is determined as the system moves within the environment and finally the egomotion...
We propose a novel framework for detecting multiple objects from a single image and reasoning about occlusions between objects. We address this problem from a 3D perspective in order to handle various occlusion patterns which can take place between objects. We introduce the concept of ``3D aspect lets'' based on a piecewise planar object representation. A 3D aspect let represents a portion of the...
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