D. Cristinacce

1.7k total citations · 1 hit paper
10 papers, 1.1k citations indexed

About

D. Cristinacce is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Computational Mechanics. According to data from OpenAlex, D. Cristinacce has authored 10 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 1 paper in Signal Processing and 1 paper in Computational Mechanics. Recurrent topics in D. Cristinacce's work include Face recognition and analysis (8 papers), Face and Expression Recognition (6 papers) and Advanced Image and Video Retrieval Techniques (3 papers). D. Cristinacce is often cited by papers focused on Face recognition and analysis (8 papers), Face and Expression Recognition (6 papers) and Advanced Image and Video Retrieval Techniques (3 papers). D. Cristinacce collaborates with scholars based in United Kingdom and United States. D. Cristinacce's co-authors include T.F. Cootes, Ian M. Scott, Nicholas Costen, John Darby and Hui Fang and has published in prestigious journals such as Pattern Recognition, Research Explorer (The University of Manchester) and INRIA a CCSD electronic archive server.

In The Last Decade

D. Cristinacce

10 papers receiving 1.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Feature Detection and Tracking with Constrained Local Models

2006 483 citations D. Cristinacce, T.F. Cootes profile →

Peers

D. Cristinacce

CVPR

SP

HI

ECP

CM

Epameinondas Antonakos United Kingdom

Xiangxin Zhu United States

Gabriele Fanelli Switzerland

Evangelos Ververas United Kingdom

Matthias Dantone Switzerland

Akshay Asthana Australia

Christos Sagonas United Kingdom

Xiangyu Zhu China

Çiğdem Eroğlu Erdem Türkiye

Epameinondas Antonakos United Kingdom

D. Cristinacce

1.0k ×1.0

CVPR

322 ×1.1

SP

97 ×0.7

HI

124 ×1.3

ECP

146 ×1.8

CM

Citations per year, relative to D. Cristinacce D. Cristinacce (= 1×) peers Epameinondas Antonakos

Countries citing papers authored by D. Cristinacce

Since Specialization

Citations

This map shows the geographic impact of D. Cristinacce's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by D. Cristinacce with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D. Cristinacce more than expected).

Fields of papers citing papers by D. Cristinacce

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D. Cristinacce. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by D. Cristinacce. The network helps show where D. Cristinacce may publish in the future.

Co-authorship network of co-authors of D. Cristinacce

This figure shows the co-authorship network connecting the top 25 collaborators of D. Cristinacce. A scholar is included among the top collaborators of D. Cristinacce based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with D. Cristinacce. D. Cristinacce is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

1.

Cristinacce, D. & T.F. Cootes. (2008). Facial Motion Analysis using Clustered Shortest Path Tree Registration. INRIA a CCSD electronic archive server. 9 indexed citations

2.

Fang, Hui, Nicholas Costen, D. Cristinacce, & John Darby. (2008). 3D Face Geometry Recovery Via Group-wise Optical Flow. 1 indexed citations

3.

Cristinacce, D. & T.F. Cootes. (2008). Automatic feature localisation with constrained local models. Pattern Recognition. 41(10). 3054–3067. 212 indexed citations

4.

Fang, Hui, Nicholas Costen, D. Cristinacce, & John Darby. (2008). 3D facial geometry recovery via group-wise optical flow. 1–6. 5 indexed citations

5.

Cristinacce, D. & T.F. Cootes. (2007). Boosted Regression Active Shape Models. Research Explorer (The University of Manchester). 79.1–79.10. 96 indexed citations

6.

Cristinacce, D. & T.F. Cootes. (2006). Facial Feature Detection and Tracking with Automatic Template Selection. Research Explorer (The University of Manchester). 429–434. 39 indexed citations

7.

Cristinacce, D. & T.F. Cootes. (2006). Feature Detection and Tracking with Constrained Local Models. 95.1–95.10. 483 indexed citations breakdown →

8.

Cristinacce, D. & T.F. Cootes. (2004). A comparison of shape constrained facial feature detectors. Research Explorer (The University of Manchester). 375–380. 45 indexed citations

9.

Cristinacce, D., T.F. Cootes, & Ian M. Scott. (2004). A Multi-Stage Approach to Facial Feature Detection. 30.1–30.10. 134 indexed citations

10.

Cristinacce, D. & T.F. Cootes. (2003). Facial feature detection using AdaBoost with shape constraints. 24.1–24.10. 83 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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