By Lourdes Agapito, Michael M. Bronstein, Carsten Rother
The four-volume set LNCS 8925, 8926, 8927, and 8928 contains the completely refereed post-workshop lawsuits of the Workshops that happened together with the thirteenth ecu convention on computing device imaginative and prescient, ECCV 2014, held in Zurich, Switzerland, in September 2014.
The 203 workshop papers have been conscientiously reviewed and chosen for inclusion within the complaints. They the place offered at workshops with the next topics: the place desktop imaginative and prescient meets artwork; desktop imaginative and prescient in motor vehicle know-how; spontaneous facial habit research; client intensity cameras for laptop imaginative and prescient; "chalearn" humans: pose, restoration, action/interaction, gesture attractiveness; video occasion categorization, tagging and retrieval in the direction of vast info; desktop imaginative and prescient with neighborhood binary development variations; visible item monitoring problem; desktop imaginative and prescient + ontology applies cross-disciplinary applied sciences; visible notion of affordance and practical visible primitives for scene research; graphical types in machine imaginative and prescient; gentle fields for desktop imaginative and prescient; machine imaginative and prescient for street scene knowing and independent riding; gentle biometrics; moving and adapting resource wisdom in computing device imaginative and prescient; surveillance and re-identification; colour and photometry in machine imaginative and prescient; assistive desktop imaginative and prescient and robotics; computing device imaginative and prescient difficulties in plant phenotyping; and non-rigid form research and deformable photo alignment. also, a panel dialogue on video segmentation is incorporated.
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Additional info for Computer Vision - ECCV 2014 Workshops: Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part II
2] utilized human pose, velocity and spatiotemporal distribution of individuals to represent the crowd context information. They further developed a system that can simultaneously track multiple people and recognize their interactions .  represented crowd context by action co-occurrence of interacting people.  proposed the Contextual Spatial Pyramid to detect the action of multiple people. g. “hug”, “push”, and “hi-ﬁve”, usually involve frequent close physical contact.  investigated interaction recognition between two people in realistic scenarios.
Shen et al. subspace using a random matrix k ×d matrix R whose columns have unit lengths. It can be represented by: (4) XRP k×N = Rk×d Xd×N As before, we apply the random projection on both motion feature and static feature to form the random feature representation. Speciﬁcally, for each extracted cuboid, we ﬁrst normalize the intensity of each pixel within the cuboid and then uniformly divide the cuboid into 2 × 2 × 2 grids. Assume the size of each grid is w × h × t pixels so for each grid we identify gray-scale vector v ∈ Rd (d = wht) by stacking the intensities; then use random projection to reduce dimensionality and form the random feature descriptor.
Shen et al. Vector of Locally Aggregated Descriptors. Besides BoF and SC, we evaluate another encoding method: vector of locally aggregated descriptors (VLAD)  for random feature representation. The idea of the VLAD is to accumulate the diﬀerence between each visual word vi and the descriptor xi which is assigned to that visual word. Note that VLAD can be viewed as a non-probabilistic version of the Fisher Vector . Therefore, if the local descriptor is d-dimensional, the dimension D of VLAD would be D = k × d.
Computer Vision - ECCV 2014 Workshops: Zurich, Switzerland, September 6-7 and 12, 2014, Proceedings, Part II by Lourdes Agapito, Michael M. Bronstein, Carsten Rother