Aim of the paper is to illustrate a paradigm shift in photonic measurements inaugurated by clustered mobile digital measurements with cloud-supported image processing for shapes, colors and spectra in visual (VIS) and non-visual ultraviolet (UV) as well as non-visual infrared (IR) ranges.

Lidar (light and radar or light detection and ranging) and SfM (structure from motion) are valuable tools for generating meshes from real world objects. In the entertainment sector these technologies come in convenient for the production. Since both methods have their advantages this paper examines the process of using both technologies in combination. Point clouds are generated using both methods and combining the results into one point cloud and creating a mesh. This generated 3D object can be used in VFX.

This paper presents a software solution of the evaluation problem faced by universities. The software consists of a REST - server application and to date an Android client. The software features automated processing of given answers, independency of location, a flexible data model supporting multiple questionnaires and an multimodal interface designed to be used effectively upon first encounter. While our approach aims to support a high participation rate of the evaluations it is currently tested in a live environment to see if it reaches this goal. Findings of these tests will be presented at the conference.

In this paper we present a novel approach for energy efficient hash table design. Hash table is a common approach to build associative arrays, database indexes and various kinds of program-defined caches. These data structures play a crucial role in modern feature-rich mobile applications. It in turn leads to significant power consumption associated with their use. However, modern hashing techniques are suffered from large probability of collision in the case of hash size acceptable for mobile devices. This makes it necessary to perform additional energy-inefficient memory access operations to resolve these collisions. We propose hashing technique with lower probability of collision for the hash of the same size. We show that unlike existing collision free approaches our hashing method has a much broader area of applicability. To support these claims both theoretical and experimental studies are presented. Experimental comparison with existing approaches has shown significant improvement of energy-efficiency for common applications.

Palmprint recognition as a novel biometric identification method for contactless mobile devices has been received substantial attentions in recent years. Palm landmark detection is one of the key technologies of palmprint identification and verification system. However, the differences of hand positions, complex backgrounds and various lighting conditions in unrestrained environment with low-resolution cameras make palm landmark detection in the wild difficult. In this paper, we proposed a new palm landmark detection approach based on Supervised Descent Method (SDM). SDM uses the relationship between the feature representation and the position of a landmark point to build an optimization problem for palm landmark detection. The optimization target function is the distance of feature representations between current position and the ideal position of a palm landmark point. After optimization, a linear function of the position displacement and the feature representation of current landmark is obtained. The linear function can be learned from palmprint image samples with labeled landmark positions. Given an input image in detection process, the initial position of a landmark is set by the mean position of the landmark in the training set, then the optimal landmark position can be calculated iteratively using the learned linear function. The effectiveness of the proposed method is proved on a mobile phone captured palm image dataset.

RECfusion is a framework devoted to the automatic processing of video data from many devices, as smartphones, tablets, webcams, surveillance cameras, etc., where all devices are thought to be connected into a 4G LTE network. Exploiting this mobile ultra-broadband connection the communication paradigm between users in the social media context can be augmented: in events like concerts, feasts, expos and so on, users become either producers than fruitors of video data. RECfusion analyzes video streams from several devices and infers semantics performing scene understanding. Key scenes are identified with relation on each video stream and all the other ones; then the system generates a video rendered from a mixage of the selected video streams. In ref. [1] a system based upon visual content popularity has been already implemented in RECfusion. In this work we propose an extension for RECfusion: a novel automatic video cluster tracking algorithm able to identify the different scenes in the gathered video streams selecting for each of them the best recording device.

More recently, the smartphone intergrated powerful camera is an efficient platform for location-wareness. The matching of smartphone recordings with a database of geo-referenced images allows for meter accurate infrastructure-free localization. However, for high accuracy indoor positioning using a smartphone, there are two constraints that includes: (1) limited computational and memory resources of smartphone; (2) user’s moving in large buildings. These constraints are also typically more severe for systems that should be wearable and used indoors. To address these issues, we proppose a novel smartphone camera-based algorithm for supporting a scalability and high accuracy indoor positiong service. In order to obtain an accurate image matching, we proppose a new feature descriptor that efficiently fused of HOG and LPQ feature. The novel feature is the local phase quantization of a salient HOG visualuizing image. The specific properties of this feature is robust in the indoor scenarios. In order to reduce the network latency and communications traffic, we introduce a basestation based indoor positiioning system for providing a coarse location. Comparing to other states of art methods, experimental results show that our algorithm allowed instantaneous camera-based indoor positioning with very low requirements on the available network connection.

The paper represents regular method of synthesis of a bit signal for the wireless communication networks using frequency manipulation for coding of the transferred information. The synthesized signal has two-level envelope and low sidelobe level in the set area of a spectrum. The synthesis method is based on repeated operations of a delay and addition of initial sequence of pulses with rectangular envelope. As a result of synthesis the signal with pulse-width modulation is obtained. Software implementation of the algorithm was created using development environment NI LabVIEW. Temporal and spectral properties of the signal are researched. The signal can also find application in Doppler's ultrasonic systems that use high-powered nonlinear amplifiers.

With the development of multimedia processing and applications, multiple types of media security and forensic have been broadly taken into consideration. The media data includes audio, video, graphic, image and etc. There are three main applications of the forensic image processing: hiding data, tampering detection and recovering of the digital information. Some artifacts and lost details on the image or video could lead to an erroneous interpretation. The objective of this paper is to ensure the production of quality forensic imagery using digital inpainting. Inpanting in images and videos aims at filling gaps (holes) occur due to instrumentation error, losses of image data during transmission. The holes may correspond to missing parts or removed objects from the scenes (logos, text, etc.). This paper includes brief descriptions of advantages, disadvantages, and potential of inpainting with applications to the forensic image processing. We present an image inpainting method based on the texture and structure propagation. It is shown that this approach allows restoring a fingerprint, missing blocks and removing a text from the scenes. Several examples considered in this paper show the effectiveness of the proposed approach for large objects removal as well as recovery of small regions on several test images and videos.