Adjacency list

About: Adjacency list is a research topic. Over the lifetime, 4419 publications have been published within this topic receiving 78449 citations.

The Constraints on Images of Rectangular Polyhedra

Abstract: This paper discusses how polyhedron interpretation techniques are simplified if the objects are rectangular trihedral polyhedra. This restriction enables one to compute the spatial orientation of a given corner and its motion from its image in terms of polar coordinates, Eulerian angles, and quaternions. One can also interpret the shape and the face adjacency from local information only. The necessary constraints are listed, and some examples are given to compare the presented scheme to existing ones. The possible nonuniqueness of the interpretation is also discussed.

Adaptive Graph Representation Learning for Video Person Re-identification

Abstract: Recent years have witnessed the remarkable progress of applying deep learning models in video person re-identification (Re-ID). A key factor for video person Re-ID is to effectively construct discriminative and robust video feature representations for many complicated situations. Part-based approaches employ spatial and temporal attention to extract representative local features. While correlations between parts are ignored in the previous methods, to leverage the relations of different parts, we propose an innovative adaptive graph representation learning scheme for video person Re-ID, which enables the contextual interactions between relevant regional features. Specifically, we exploit the pose alignment connection and the feature affinity connection to construct an adaptive structure-aware adjacency graph, which models the intrinsic relations between graph nodes. We perform feature propagation on the adjacency graph to refine regional features iteratively, and the neighbor nodes' information is taken into account for part feature representation. To learn compact and discriminative representations, we further propose a novel temporal resolution-aware regularization, which enforces the consistency among different temporal resolutions for the same identities. We conduct extensive evaluations on four benchmarks, i.e. iLIDS-VID, PRID2011, MARS, and DukeMTMC-VideoReID, experimental results achieve the competitive performance which demonstrates the effectiveness of our proposed method. The code is available at this https URL.

A word graph based N-best search in continuous speech recognition

Abstract: The authors introduce an efficient algorithm for the exhaustive search of N-best sentence hypotheses in a word graph. The search procedure is based on a two-pass algorithm. In the first pass, a word graph is constructed with standard time-synchronous beam search. The actual extraction of N-best word sequences from the word graph takes place during the second pass. With the implementation of a tree-organized N-best list, the search is performed directly on the resulting word graph. Therefore, the parallel bookkeeping of N hypotheses at each processing step during the search is not necessary. It is important to point out that the proposed N-best search algorithm produces an exact N-best list as defined by the word graph structure. Possible errors can only result from pruning during the construction of the word graph. In a postprocessing step, the N candidates can be rescored with a more complex language model with highly reduced computational cost. This algorithm is also applied in speech understanding to select the most likely sentence hypothesis that satisfies some additional constraints.

System for mapping logical functional test data of logical integrated circuits to physical representation using pruned diagnostic list

Abstract: An improved method for mapping logical function test data of logical integrated circuits to physical representations uses a pruned diagnostic list. The steps include creating a final logical diagnostic list of potential bridging faults in response to testing the circuit for stuck-at faults at a plurality of nets of the circuit, receiving the physical data associated with nets of the circuit, applying adjacency criteria to the physical data, generating a pruned diagnostic list of potential bridging faults in response to applying the adjacency criteria, performing in-line inspection to obtain second localized probable defect data and correlating second localized portable defect data with the pruned diagnostic list.