| 135 | -- | 0 | Rainer Stiefelhagen, Marian Stewart Bartlett, Kevin W. Bowyer. Best of Automatic Face and Gesture Recognition 2011 |
| 136 | -- | 146 | Xiaowei Zhao, Xiujuan Chai, Zhiheng Niu, Cherkeng Heng, Shiguang Shan. Context modeling for facial landmark detection based on Non-Adjacent Rectangle (NAR) Haar-like feature |
| 147 | -- | 158 | Yuki Oka, Takeshi Shakunaga. Real-time face tracking and recognition by sparse eigentracker with associative mapping to 3D shape |
| 159 | -- | 168 | Nicolas Pinto, David D. Cox. High-throughput-derived biologically-inspired features for unconstrained face recognition |
| 169 | -- | 176 | Alice J. O'Toole, P. Jonathon Phillips, Xiaobo An, Joseph P. Dunlop. Demographic effects on estimates of automatic face recognition performance |
| 177 | -- | 185 | P. Jonathon Phillips, J. Ross Beveridge, Bruce A. Draper, Geof H. Givens, Alice J. O'Toole, David S. Bolme, Joseph P. Dunlop, Yui Man Lui, Hassan Sahibzada, Samuel Weimer. The Good, the Bad, and the Ugly Face Challenge Problem |
| 186 | -- | 196 | Mihalis A. Nicolaou, Hatice Gunes, Maja Pantic. Output-associative RVM regression for dimensional and continuous emotion prediction |
| 197 | -- | 205 | Patrick Lucey, Jeffrey F. Cohn, Kenneth M. Prkachin, Patricia E. Solomon, Sien W. Chew, Iain Matthews. Painful monitoring: Automatic pain monitoring using the UNBC-McMaster shoulder pain expression archive database |
| 206 | -- | 216 | Stephen O'Hara, Yui Man Lui, Bruce A. Draper. Using a Product Manifold distance for unsupervised action recognition |
| 217 | -- | 226 | Loren Arthur Schwarz, Artashes Mkhitaryan, Diana Mateus, Nassir Navab. Human skeleton tracking from depth data using geodesic distances and optical flow |
| 227 | -- | 235 | Xiaohui Shen, Gang Hua, Lance Williams, Ying Wu. Dynamic hand gesture recognition: An exemplar-based approach from motion divergence fields |
| 236 | -- | 250 | Victor Adrian Prisacariu, Ian Reid. 3D hand tracking for human computer interaction |
| 251 | -- | 261 | Gutemberg Guerra-Filho, Arnab Biswas. The human motion database: A cognitive and parametric sampling of human motion |