7,671 research outputs found
An Octree-Based Approach towards Efficient Variational Range Data Fusion
Volume-based reconstruction is usually expensive both in terms of memory
consumption and runtime. Especially for sparse geometric structures, volumetric
representations produce a huge computational overhead. We present an efficient
way to fuse range data via a variational Octree-based minimization approach by
taking the actual range data geometry into account. We transform the data into
Octree-based truncated signed distance fields and show how the optimization can
be conducted on the newly created structures. The main challenge is to uphold
speed and a low memory footprint without sacrificing the solutions' accuracy
during optimization. We explain how to dynamically adjust the optimizer's
geometric structure via joining/splitting of Octree nodes and how to define the
operators. We evaluate on various datasets and outline the suitability in terms
of performance and geometric accuracy.Comment: BMVC 201
An Immersive Telepresence System using RGB-D Sensors and Head Mounted Display
We present a tele-immersive system that enables people to interact with each
other in a virtual world using body gestures in addition to verbal
communication. Beyond the obvious applications, including general online
conversations and gaming, we hypothesize that our proposed system would be
particularly beneficial to education by offering rich visual contents and
interactivity. One distinct feature is the integration of egocentric pose
recognition that allows participants to use their gestures to demonstrate and
manipulate virtual objects simultaneously. This functionality enables the
instructor to ef- fectively and efficiently explain and illustrate complex
concepts or sophisticated problems in an intuitive manner. The highly
interactive and flexible environment can capture and sustain more student
attention than the traditional classroom setting and, thus, delivers a
compelling experience to the students. Our main focus here is to investigate
possible solutions for the system design and implementation and devise
strategies for fast, efficient computation suitable for visual data processing
and network transmission. We describe the technique and experiments in details
and provide quantitative performance results, demonstrating our system can be
run comfortably and reliably for different application scenarios. Our
preliminary results are promising and demonstrate the potential for more
compelling directions in cyberlearning.Comment: IEEE International Symposium on Multimedia 201
Perceptually optimized real-time computer graphics
Perceptual optimization, the application of human visual perception models to remove imperceptible components in a graphics system, has been proven effective in achieving significant computational speedup. Previous implementations of this technique have focused on spatial level of detail reduction, which typically results in noticeable degradation of image quality. This thesis introduces refresh rate modulation (RRM), a novel perceptual optimization technique that produces better performance enhancement while more effectively preserving image quality and resolving static scene elements in full detail. In order to demonstrate the effectiveness of this technique, a graphics framework has been developed that interfaces with eye tracking hardware to take advantage of user fixation data in real-time. Central to the framework is a high-performance GPGPU ray-tracing engine written in OpenCL. RRM reduces the frequency with which pixels outside of the foveal region are updated by the ray-tracer. A persistent pixel buffer is maintained such that peripheral data from previous frames provides context for the foveal image in the current frame. Traditional optimization techniques have also been incorporated into the ray-tracer for improved performance. Applying the RRM technique to the ray-tracing engine results in a speedup of 2.27 (252 fps vs. 111 fps at 1080p) for the classic Whitted scene with reflection and transmission enabled. A speedup of 3.41 (140 fps vs. 41 fps at 1080p) is observed for a high-polygon scene that depicts the Stanford Bunny. A small pilot study indicates that RRM achieves these results with minimal impact to perceived image quality. A secondary investigation is conducted regarding the performance benefits of increasing physics engine error tolerance for bounding volume hierarchy based collision detection when the scene elements involved are in the user\u27s periphery. The open-source Bullet Physics Library was used to add accurate collision detection to the full resolution ray-tracing engine. For a scene with a static high-polygon model and 50 moving spheres, a speedup of 1.8 was observed for physics calculations. The development and integration of this subsystem demonstrates the extensibility of the graphics framework
Multi-View Reconstruction in-between Known Environments
AbstractâWe present a novel multi-view 3D reconstruction algorithm which unifies the advantages of several recent reconstruction approaches. Based on a known environment causing occlusions and on the cameras ' pixel grid discretization, an irregular partitioning of the reconstruction space is chosen. Reconstruction artifacts are rejected by using plausibility checks based on additional information about the objects to be reconstructed. The binary occupancy decision is solely performed in reconstruction space instead of fusing back-projected silhouettes in image space. Hierarchical data structures are used to reconstruct the objects progressively focusing on boundary regions. Thus, the algorithm can be stopped at any time with a certain conservative level of detail. Most parts of the algorithm may be processed in parallel using GPU programming techniques. The main application domain is the surveillance of real environments like in human/robot coexistence and cooperation scenarios
Label Space Partition Selection for Multi-Object Tracking Using Two-Layer Partitioning
Estimating the trajectories of multi-objects poses a significant challenge
due to data association ambiguity, which leads to a substantial increase in
computational requirements. To address such problems, a divide-and-conquer
manner has been employed with parallel computation. In this strategy,
distinguished objects that have unique labels are grouped based on their
statistical dependencies, the intersection of predicted measurements. Several
geometry approaches have been used for label grouping since finding all
intersected label pairs is clearly infeasible for large-scale tracking
problems. This paper proposes an efficient implementation of label grouping for
label-partitioned generalized labeled multi-Bernoulli filter framework using a
secondary partitioning technique. This allows for parallel computation in the
label graph indexing step, avoiding generating and eliminating duplicate
comparisons. Additionally, we compare the performance of the proposed technique
with several efficient spatial searching algorithms. The results demonstrate
the superior performance of the proposed approach on large-scale data sets,
enabling scalable trajectory estimation.Comment: 6 pages, 4 figure
Review of Person Re-identification Techniques
Person re-identification across different surveillance cameras with disjoint
fields of view has become one of the most interesting and challenging subjects
in the area of intelligent video surveillance. Although several methods have
been developed and proposed, certain limitations and unresolved issues remain.
In all of the existing re-identification approaches, feature vectors are
extracted from segmented still images or video frames. Different similarity or
dissimilarity measures have been applied to these vectors. Some methods have
used simple constant metrics, whereas others have utilised models to obtain
optimised metrics. Some have created models based on local colour or texture
information, and others have built models based on the gait of people. In
general, the main objective of all these approaches is to achieve a
higher-accuracy rate and lowercomputational costs. This study summarises
several developments in recent literature and discusses the various available
methods used in person re-identification. Specifically, their advantages and
disadvantages are mentioned and compared.Comment: Published 201
- âŠ