The state of Kerala in India has seen multiple instances of intense cyclones in recent years, resulting in heavy flooding. One of the biggest challenges faced by rescuers is the accessibility to flooded areas and buildings during rescue ...$$$$$\mathrm{}$

While recovery of geometry from image and video data has received a lot of attention in computer vision, methods to capture the texture for a given geometry are less mature. Specifically, classical methods for texture generation often assume clean ...

While recovery of geometry from image and video data has received a lot of attention in computer vision, methods to capture the texture for a given geometry are less mature. Specifically, classical methods for texture generation often assume clean ...

This work introduces a ultra-fast object detection method named FLA-CNN for detecting objects in a scene from a planar LIDAR signal, using convolutional Neural Networks (CNN). Compared with recent methods using CNN on 2D/3D lidar scene ...

Contemporary machine learning literature highlights learning object-centric image representations’ benefits, i.e. interpretability, and the improved generalization performance. In the current work, we develop a neural network architecture that ...

The domain of spatial audio comprises methods for capturing, processing, and reproducing audio content that contains spatial information. Data-based methods are those that operate directly on the spatial information carried by audio signals. This ...

Continuity of care is achieved in the neonatal intensive care unit (NICU) through careful documentation of all events of clinical significance, including clinical interventions and routine care events (e.g., feeding, diaper change, weighing, etc.)...

• Multi-faceted and multi-modal computer vision for complex scene understanding in the neonatal intensive care unit (NICU).
• Proof-of-concept textual summary generation of a clinical NICU scene as a step towards semi-automated nurse ...

With ubiquitous cameras and popular 3D scanning and capturing devices to help us capture 2D/3D scene data, there are many scene understanding related applications, as well as quite a few important and interesting research problems in processing, ...

Aiming at the problem of object recognition caused by small object scale, multi-interaction (occlusion), and strong hiding characteristics in the scene analysis task, an object-region-enhanced network based on deep learning was proposed. The ...

We propose a novel hierarchy construction algorithm for 3D scenes with repeated elements, such as classrooms with multiple desk–chair pairs. Most existing algorithms focus on scenes such as bedrooms or living rooms, which rarely contain repeated ...

• En-HMAX adopts a relative order of importance depending on the image category.
• ...

The human visual recognition system is more efficient than any current robotic vision setting. One reason for this superiority is that humans utilize different fields of vision, depending on the recognition task. For instance, ...

Scene recognition is an important and challenging problem in computer vision. One of the most used scene recognition methods is the bag-of-visual words. Despite the interesting results, this approach does not capture the detail richness of spatial ...

Along with the rapid development of autonomous vehicles and driving assistance systems, suitable maps have been intensively studied in recent years. Besides the improvement of conventional maps, new types such as high-density (HD) maps, have been ...

In this paper, texture probabilistic grammar is defined for the first time. We have developed an algorithm to obtain the 3D information in a 2D scene by training the texture probabilistic grammar from the prebuilt model library. The well-trained texture ...

Content based video indexing and retrieval (CBVIR) is a lively area of research which focuses on automating the indexing, retrieval and management of videos. This area has a wide spectrum of promising applications where assessing the impact of ...

Every day, a huge amount of video data is generated worldwide and processing this kind of data requires powerful resources in terms of time, manpower, and hardware. Therefore, to help quickly understand the content of video data, video summarization ...

Applications, such as construction monitoring and planning for renovations, require the accurate recovery of existing conditions of structures. Many types of infrastructure are primarily comprised of arbitrarily-shaped thin structures (e.g., Truss ...

Efficient 2D LSTM attribute learning without pre-/post- processing of the data.2D LSTM networks with only a small amount of parameters.Raw noisy web-images for training without manual annotation.Automatic web-image analysis (unknown number of attribute ...

In this paper, we propose a probabilistic approach to generate abstract scene graphs from uncertain 6D pose estimates. We focus on generating a semantic understanding of the perceived scenes that well explains the composition of the scene and the inter-...

We present a system to easily capture building interiors and automatically generate floor plans scaled to their metric dimensions. The proposed approach is able to manage scenes not necessarily limited to the Manhattan World assumption, exploiting the ...