Frequency-Based Motion Representation for Video Generative Adversarial Networks.

Videos contain motions of various speeds. For example, the motions of one's head and mouth differ in terms of speed - the head being relatively stable and the mouth moving rapidly as one speaks. Despite its diverse nature, previous video GANs generate video based on a single unified motion representation without considering the aspect of speed. In this paper, we propose a frequency-based motion representation for video GANs to realize the concept of speed in video generation process. In detail, we represent motions as continuous sinusoidal signals of various frequencies by introducing a coordinate-based motion generator. We show, in that case, frequency is highly related to the speed of motion. Based on this observation, we present frequency-aware weight modulation that enables manipulation of motions within a specific range of speed, which could not be achieved with the previous techniques. Extensive experiments validate that the proposed method outperforms state-of-the-art video GANs in terms of generation quality by its capability to model various speed of motions. Furthermore, we also show that our temporally continuous representation enables to further synthesize intermediate and future frames of generated videos.

Development of an Antiwindup Technique for a Cascade Control System.

A cascade control system comprising the primary and secondary controllers suffers from a cascade-type integral windup problem in which the output saturation of the secondary control loop can considerably increase the integral part of the primary control loop. In this paper, we present a new predictive antiwindup technique that can completely eliminate the possibility of secondary controller output saturation, resulting in no cascade-type integral windup phenomenon. The proposed method does not require any type of process models; thus, its implementation is simple and straightforward, which is a very favorable advantage compared to the model-based antiwindup techniques from the practical viewpoint. Our simulation confirms that the proposed method can completely remove the primary controller's cascade-type integral windup resulting from the saturation of the secondary controller output. Further, the proposed method exhibited good control performance without needing any type of process model for the various types of processes and controllers. Our experimental study successfully demonstrated that there are no problems in applying the proposed method to real plants.

Distance Encoded Product Quantization for Approximate K-Nearest Neighbor Search in High-Dimensional Space.

Approximate K-nearest neighbor search is a fundamental problem in computer science. The problem is especially important for high-dimensional and large-scale data. Recently, many techniques encoding high-dimensional data to compact codes have been proposed. The product quantization and its variations that encode the cluster index in each subspace have been shown to provide impressive accuracy. In this paper, we explore a simple question: is it best to use all the bit-budget for encoding a cluster index? We have found that as data points are located farther away from the cluster centers, the error of estimated distance becomes larger. To address this issue, we propose a novel compact code representation that encodes both the cluster index and quantized distance between a point and its cluster center in each subspace by distributing the bit-budget. We also propose two distance estimators tailored to our representation. We further extend our method to encode global residual distances in the original space. We have evaluated our proposed methods on benchmarks consisting of GIST, VLAD, and CNN features. Our extensive experiments show that the proposed methods significantly and consistently improve the search accuracy over other tested techniques. This result is achieved mainly because our methods accurately estimate distances.

Content-Aware Focal Plane Selection and Proposals for Object Tracking on Plenoptic Image Sequences.

Object tracking is a fundamental problem in computer vision since it is required in many practical applications including video-based surveillance and autonomous vehicles. One of the most challenging scenarios in the problem is when the target object is partially or even fully occluded by other objects. In such cases, most of existing trackers can fail in their task while the object is invisible. Recently, a few techniques have been proposed to tackle the occlusion problem by performing the tracking on plenoptic image sequences. Although they have shown promising results based on the refocusing capability of plenoptic images, there is still room for improvement. In this paper, we propose a novel focus index selection algorithm to identify an optimal focal plane where the tracking should be performed. To determine an optimal focus index, we use a focus measure to find maximally focused plane and a visual similarity to capture the plane where the target object is visible, and its appearance is distinguishably clear. We further use the selected focus index to generate proposals. Since the optimal focus index allows us to estimate the distance between the camera and the target object, we can more accurately guess the scale changes of the object in the image plane. Our proposal algorithm also takes the trajectory of the target object into account. We extensively evaluate our proposed techniques on three plenoptic image sequences by comparing them against the prior tracking methods specialized to the plenoptic image sequences. In experiments, our method provides higher accuracy and robustness over the prior art, and those results confirm that the merits of our proposed algorithms.

Spherical hashing: binary code embedding with hyperspheres.

Many binary code embedding schemes have been actively studied recently, since they can provide efficient similarity search, and compact data representations suitable for handling large scale image databases. Existing binary code embedding techniques encode high-dimensional data by using hyperplane-based hashing functions. In this paper we propose a novel hypersphere-based hashing function, spherical hashing, to map more spatially coherent data points into a binary code compared to hyperplane-based hashing functions. We also propose a new binary code distance function, spherical Hamming distance, tailored for our hypersphere-based binary coding scheme, and design an efficient iterative optimization process to achieve both balanced partitioning for each hash function and independence between hashing functions. Furthermore, we generalize spherical hashing to support various similarity measures defined by kernel functions. Our extensive experiments show that our spherical hashing technique significantly outperforms state-of-the-art techniques based on hyperplanes across various benchmarks with sizes ranging from one to 75 million of GIST, BoW and VLAD descriptors. The performance gains are consistent and large, up to 100 percent improvements over the second best method among tested methods. These results confirm the unique merits of using hyperspheres to encode proximity regions in high-dimensional spaces. Finally, our method is intuitive and easy to implement.

Genetic association of phosphodiesterase 1B (PDE1B) with carcass traits in Korean cattle.

Quantitative trait loci for fat deposition and carcass traits have been identified in the vicinity of the gene encoding phosphodiesterase 1B (PDE1B) on bovine chromosome 5. Therefore, the PDE1B gene can be considered as a positional and functional candidate gene for carcass traits in beef cattle. This study aimed to identify single nucleotide polymorphisms (SNPs) in the PDE1B gene and to evaluate their associations with carcass traits in Korean cattle. Eight SNPs, g.440T>G, g.17122A>G, g.17507A>C, g.17575A>G, g.17607T>C, g.17609C>A, g.17692C>T, and g.17707C>G, were identified in the region ranged from exon 1 to intron 6. Five of them were used for association analysis because of their availability of restriction fragment length polymorphisms. As a result, g.17122A>G in intron 3 was significantly associated with backfat thickness (BFT), and g.17507A>C in exon 5 was associated with longissimus dorsi muscle area (LMA, P < 0.05). Animals with the AG genotype of g.17122 had thicker BFT than those with the AA genotype. Animals with the AA or AC genotype of g.17507A>C had larger LMA than those with the CC genotype. We suggested the PDE1B gene as a candidate gene for carcass traits of beef cattle. Fine mapping would be required for application to marker-assisted selection.

Genetic variants of the FABP4 gene are associated with marbling scores and meat quality grades in Hanwoo (Korean cattle).

This study was aimed to search new genetic variants in the bovine FABP4 gene as molecular markers for meat quality and carcass traits. PCR-RFLP analysis revealed that three SNPs located at nucleotide positions g.2834C>G, g.3533T>A, and g.3691G>A were identified based on a GenBank accession number (NC_007312.4). Sequence analysis revealed that SNPs were located in intron 1 (g.2834C>G) and 2 (g.3533T>A), and an exon 3 (g.3691G>A), showing allele frequencies as 0.592, 0.579, and 0.789, respectively. Genetic variabilities of heterozygosity (He) and polymorphic information contents (PIC) were estimated for g.2834C>G (0.608 and 0.531), g.3533T>A (0.615 and 0.539), and g.3691G>A (0.498 and 0.401) loci, respectively. A SNP located in the exon 3 of FABP4 was characterized and associated with desirable increases of MS (marbling scores) and MG (meat quality grades) in Hanwoo. The statistical analysis revealed that additive effects by GG genotypes in g.3691G>A SNP were significantly greater than AA genotypes in MS and MG traits. These findings suggest that the FABP4g.3691G>A SNP will be a useful candidate locus to maximize economic benefits for cattle populations.