Enhanced Trajectory-based Action Recognition using Human Pose

in IEEE International Conference on Image Processing, Beijing 17-20 Spetember 2017 (2017)

Action recognition using dense trajectories is a popular concept. However, many spatio-temporal characteristics of the trajectories are lost in the final video representation when using a single Bag-of ... [more ▼]

Action recognition using dense trajectories is a popular concept. However, many spatio-temporal characteristics of the trajectories are lost in the final video representation when using a single Bag-of-Words model. Also, there is a significant amount of extracted trajectory features that are actually irrelevant to the activity being analyzed, which can considerably degrade the recognition performance. In this paper, we propose a human-tailored trajectory extraction scheme, in which trajectories are clustered using information from the human pose. Two configurations are considered; first, when exact skeleton joint positions are provided, and second, when only an estimate thereof is available. In both cases, the proposed method is further strengthened by using the concept of local Bag-of-Words, where a specific codebook is generated for each skeleton joint group. This has the advantage of adding spatial human pose awareness in the video representation, effectively increasing its discriminative power. We experimentally compare the proposed method with the standard dense trajectories approach on two challenging datasets. [less ▲]

Unsupervised Vanishing Point Detection and Camera Calibration from a Single Manhattan Image with Radial Distortion

in IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 (2017)

The article concerns the automatic calibration of a camera with radial distortion from a single image. It is known that, under the mild assumption of square pixels and zero skew, lines in the scene ... [more ▼]

The article concerns the automatic calibration of a camera with radial distortion from a single image. It is known that, under the mild assumption of square pixels and zero skew, lines in the scene project into circles in the image, and three lines suffice to calibrate the camera up to an ambiguity between focal length and radial distortion. The calibration results highly depend on accurate circle estimation, which is hard to accomplish, because lines tend to project into short circular arcs. To overcome this problem, we show that, given a short circular arc edge, it is possible to robustly determine a line that goes through the center of the corresponding circle. These lines, henceforth called Lines of Circle Centres (LCCs), are used in a new method that detects sets of parallel lines and estimates the calibration parameters, including the center and amount of distortion, focal length, and camera orientation with respect to the Manhattan frame. Extensive experiments in both semi-synthetic and real images show that our algorithm outperforms state- of-the-art approaches in unsupervised calibration from a single image, while providing more information. [less ▲]

Visual and human-interpretable feedback for assisting physical activity

in European Conference on Computer Vision (ECCV) Workshop on Assistive Computer Vision and Robotics Amsterdam, (2016)

Physical activity is essential for stroke survivors for recovering some autonomy in daily life activities. Post-stroke patients are initially subject to physical therapy under the supervision of a health ... [more ▼]

Physical activity is essential for stroke survivors for recovering some autonomy in daily life activities. Post-stroke patients are initially subject to physical therapy under the supervision of a health professional, but due to economical aspects, home based rehabilitation is eventually suggested. In order to support the physical activity of stroke patients at home, this paper presents a system for guiding the user in how to properly perform certain actions and movements. This is achieved by presenting feedback in form of visual information and human-interpretable messages. The core of the proposed approach is the analysis of the motion required for aligning body-parts with respect to a template skeleton pose, and how this information can be presented to the user in form of simple recommendations. Experimental results in three datasets show the potential of the proposed framework. [less ▲]

RGB-D and Thermal Sensor Fusion

in 11th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISAPP) (2016)

Distributed Dense Stereo Matching for 3D Reconstruction using Parallel-based Processing Advantages

in Proc. of the 40th International Conference on Acoustics, Speech and Signal Processing (ICASSP) (2015)

Piecewise-Planar StereoScan: Structure and Motion from Plane Primitives

in European Conference on Computer Vision (ECCV) (2014, September)

SymStereo: Stereo Matching using Induced Symmetry

in International Journal of Computer Vision (2014)

Unsupervised intrinsic calibration from a single frame using a "plumb-line" approach

in International Conference on Computer Vision (ICCV) (2013, December)

Efficient Stereo Matching using Histogram Aggregation with Multiple Slant Hypothesis

in 6th Iberian Conference on Pattern Recognition and Image Analysis (IbPria) (2013, June)

Semi-dense piecewise planar stereo reconstruction using SymStereo and PEARL

in 3DimPVT (2012, October)