24 research outputs found
HB-net: Holistic bursting cell cluster integrated network for occluded multi-objects recognition
Within the realm of image recognition, a specific category of multi-label
classification (MLC) challenges arises when objects within the visual field may
occlude one another, demanding simultaneous identification of both occluded and
occluding objects. Traditional convolutional neural networks (CNNs) can tackle
these challenges; however, those models tend to be bulky and can only attain
modest levels of accuracy. Leveraging insights from cutting-edge neural science
research, specifically the Holistic Bursting (HB) cell, this paper introduces a
pioneering integrated network framework named HB-net. Built upon the foundation
of HB cell clusters, HB-net is designed to address the intricate task of
simultaneously recognizing multiple occluded objects within images. Various
Bursting cell cluster structures are introduced, complemented by an evidence
accumulation mechanism. Testing is conducted on multiple datasets comprising
digits and letters. The results demonstrate that models incorporating the HB
framework exhibit a significant enhancement in recognition accuracy
compared to models without the HB framework ( times, ).
Although in high-noise settings, standard CNNs exhibit slightly greater
robustness when compared to HB-net models, the models that combine the HB
framework and EA mechanism achieve a comparable level of accuracy and
resilience to ResNet50, despite having only three convolutional layers and
approximately of the parameters. The findings of this study offer
valuable insights for improving computer vision algorithms. The essential code
is provided at https://github.com/d-lab438/hb-net.git
Exploiting Spatio-Temporal Coherence for Video Object Detection in Robotics
This paper proposes a method to enhance video object detection for indoor environments in robotics. Concretely, it exploits knowledge about the camera motion between frames to propagate previously detected objects to successive frames. The proposal is rooted in the concepts of planar homography to propose regions of interest where to find objects, and recursive Bayesian filtering to integrate observations over time. The proposal is evaluated on six virtual, indoor environments, accounting for the detection of nine object classes over a total of ∼ 7k frames. Results show that our proposal improves the recall and the F1-score by a factor of 1.41 and 1.27, respectively, as well as it achieves a significant reduction of the object categorization entropy (58.8%) when compared to a two-stage video object detection method used as baseline, at the cost of small time overheads (120 ms) and precision loss (0.92).</p
Computer Vision for Multimedia Geolocation in Human Trafficking Investigation: A Systematic Literature Review
The task of multimedia geolocation is becoming an increasingly essential
component of the digital forensics toolkit to effectively combat human
trafficking, child sexual exploitation, and other illegal acts. Typically,
metadata-based geolocation information is stripped when multimedia content is
shared via instant messaging and social media. The intricacy of geolocating,
geotagging, or finding geographical clues in this content is often overly
burdensome for investigators. Recent research has shown that contemporary
advancements in artificial intelligence, specifically computer vision and deep
learning, show significant promise towards expediting the multimedia
geolocation task. This systematic literature review thoroughly examines the
state-of-the-art leveraging computer vision techniques for multimedia
geolocation and assesses their potential to expedite human trafficking
investigation. This includes a comprehensive overview of the application of
computer vision-based approaches to multimedia geolocation, identifies their
applicability in combating human trafficking, and highlights the potential
implications of enhanced multimedia geolocation for prosecuting human
trafficking. 123 articles inform this systematic literature review. The
findings suggest numerous potential paths for future impactful research on the
subject
Development of an augmented reality guided computer assisted orthopaedic surgery system
Previously held under moratorium from 1st December 2016 until 1st December 2021.This body of work documents the developed of a proof of concept augmented reality
guided computer assisted orthopaedic surgery system – ARgCAOS.
After initial investigation a visible-spectrum single camera tool-mounted tracking
system based upon fiducial planar markers was implemented. The use of
visible-spectrum cameras, as opposed to the infra-red cameras typically used by
surgical tracking systems, allowed the captured image to be streamed to a display in
an intelligible fashion. The tracking information defined the location of physical
objects relative to the camera. Therefore, this information allowed virtual models to
be overlaid onto the camera image. This produced a convincing augmented
experience, whereby the virtual objects appeared to be within the physical world,
moving with both the camera and markers as expected of physical objects.
Analysis of the first generation system identified both accuracy and graphical
inadequacies, prompting the development of a second generation system. This too
was based upon a tool-mounted fiducial marker system, and improved performance
to near-millimetre probing accuracy. A resection system was incorporated into the
system, and utilising the tracking information controlled resection was performed,
producing sub-millimetre accuracies.
Several complications resulted from the tool-mounted approach. Therefore, a third
generation system was developed. This final generation deployed a stereoscopic
visible-spectrum camera system affixed to a head-mounted display worn by the user.
The system allowed the augmentation of the natural view of the user, providing
convincing and immersive three dimensional augmented guidance, with probing and
resection accuracies of 0.55±0.04 and 0.34±0.04 mm, respectively.This body of work documents the developed of a proof of concept augmented reality
guided computer assisted orthopaedic surgery system – ARgCAOS.
After initial investigation a visible-spectrum single camera tool-mounted tracking
system based upon fiducial planar markers was implemented. The use of
visible-spectrum cameras, as opposed to the infra-red cameras typically used by
surgical tracking systems, allowed the captured image to be streamed to a display in
an intelligible fashion. The tracking information defined the location of physical
objects relative to the camera. Therefore, this information allowed virtual models to
be overlaid onto the camera image. This produced a convincing augmented
experience, whereby the virtual objects appeared to be within the physical world,
moving with both the camera and markers as expected of physical objects.
Analysis of the first generation system identified both accuracy and graphical
inadequacies, prompting the development of a second generation system. This too
was based upon a tool-mounted fiducial marker system, and improved performance
to near-millimetre probing accuracy. A resection system was incorporated into the
system, and utilising the tracking information controlled resection was performed,
producing sub-millimetre accuracies.
Several complications resulted from the tool-mounted approach. Therefore, a third
generation system was developed. This final generation deployed a stereoscopic
visible-spectrum camera system affixed to a head-mounted display worn by the user.
The system allowed the augmentation of the natural view of the user, providing
convincing and immersive three dimensional augmented guidance, with probing and
resection accuracies of 0.55±0.04 and 0.34±0.04 mm, respectively
Enabling the Development and Implementation of Digital Twins : Proceedings of the 20th International Conference on Construction Applications of Virtual Reality
Welcome to the 20th International Conference on Construction Applications of Virtual Reality (CONVR 2020). This year we are meeting on-line due to the current Coronavirus pandemic. The overarching theme for CONVR2020 is "Enabling the development and implementation of Digital Twins". CONVR is one of the world-leading conferences in the areas of virtual reality, augmented reality and building information modelling. Each year, more than 100 participants from all around the globe meet to discuss and exchange the latest developments and applications of virtual technologies in the architectural, engineering, construction and operation industry (AECO). The conference is also known for having a unique blend of participants from both academia and industry. This year, with all the difficulties of replicating a real face to face meetings, we are carefully planning the conference to ensure that all participants have a perfect experience. We have a group of leading keynote speakers from industry and academia who are covering up to date hot topics and are enthusiastic and keen to share their knowledge with you. CONVR participants are very loyal to the conference and have attended most of the editions over the last eighteen editions. This year we are welcoming numerous first timers and we aim to help them make the most of the conference by introducing them to other participants
Proceedings of the 9th Arab Society for Computer Aided Architectural Design (ASCAAD) international conference 2021 (ASCAAD 2021): architecture in the age of disruptive technologies: transformation and challenges.
The ASCAAD 2021 conference theme is Architecture in the age of disruptive technologies: transformation and challenges. The theme addresses the gradual shift in computational design from prototypical morphogenetic-centered associations in the architectural discourse. This imminent shift of focus is increasingly stirring a debate in the architectural community and is provoking a much needed critical questioning of the role of computation in architecture as a sole embodiment and enactment of technical dimensions, into one that rather deliberately pursues and embraces the humanities as an ultimate aspiration