Movielogr

Home

movie poster

Rating: 8 stars

Seen 1 time

Seen on: 11/26/2011

View on: IMDb | TMDb

Hugo (2011)

Directed by Martin Scorsese

Adventure

Most recently watched by sensoria

Overview

Orphaned and alone except for an uncle, Hugo Cabret lives in the walls of a train station in 1930s Paris. Hugo’s job is to oil and maintain the station’s clocks, but to him, his more important task is to protect a broken automaton and notebook left to him by his late father. Accompanied by the goddaughter of an embittered toy merchant, Hugo embarks on a quest to solve the mystery of the automaton and find a place he can call home.

Rated PG | Length 126 minutes

Actors

Christopher Lee | Martin Scorsese | Emily Mortimer | Angus Barnett | Ben Kingsley | Ray Winstone | Sacha Baron Cohen | Jude Law | Michael Pitt | Richard Griffiths | Helen McCrory | Kevin Eldon | Frances de la Tour | Chloë Grace Moretz | Michael Stuhlbarg | Asa Butterfield | Marco Aponte | Gulliver McGrath | Brian Selznick | Christos Lawton | Edmund Kingsley | Ed Sanders | Max Wrottesley | Graham Curry | Hugo Malpeyre | Gino Picciano | Ben Addis | Eric Haldezos | Francesca Scorsese | Frederick Warder | Max Cane | Shaun Aylward | Frank Bourke | Ilona Cheshire | Terence Frisch | Robert Gill | Stephen Box | Tomos James | Lily Carlson | Emily Surgent | Emil Lager

Viewing Notes

I get tired of people telling me what I should and shouldn’t like. I also get tired of people telling me what is and isn’t a good film for children.

My wife had read (yes, as in out loud, at bedtime) the book Hugo Cabret, to my sons, who both enjoyed it, as did she. Because they’d read the book, they both were interested in seeing the film. My interest in seeing it had more to do with Scorsese directing it than anything else.

I try to go into most films at the theater without reading any reviews, fawning over endless set shots, reading interviews with the stars, etc. However, some films garner so much attention on Twitter that it’s hard to avoid everything. So I’d read a lot of hugely favorable 140 character opinions, and seen some ugly back and forth about the film’s use of 3D, as well.

I’ll just state that I’m not a fan of 3D generally. I thought it was used well in two movies I’ve seen: the beautifully animated Coraline, and the over-the-top Avatar. (I’ve since watched Avatar in 2D on BluRay and I don’t think the film suffers any from lack of 3D)

Because of what I’d read on Twitter, I decided to take my family to the 3D showing of Hugo, and I’m glad that I did. I thought Scorsese’s use of 3D throughout the film was excellent. I especially admired it during the recreation scenes of old films (and by old, I mean from before WWI; before Hollywood).

I liked the movie a lot; it’s an ode to the history of cinema, as well as a cautionary reminder that we need to preserve this rich cultural heritage that has been bestowed upon us. I admire that Scorsese embraced, and used well, a new technology for not only telling the tale, but for moving that very history of cinema an additional step forward, at least in his eyes.

Only time will tell us whether 3D turns out to be another technical milestone for the better in the history of cinema. Despite my doubts, Scorsese certainly makes his case for it eloquently.

As it stands, my opinion is that this film is one of those “hold close to your hearts” minor masterpieces. In Scorsese’s legacy, I do not think that Hugo will overshadow Taxi Driver or Raging Bull or… you get the idea.

Personally, I enjoyed the film a lot because I love film. I’ve not watched a lot of silent era films, though I’ve seen many, many clips and stills from them when I took my film history class in college and in the many years since. For those reasons, I enjoyed the movie. It was nostalgic and beautiful and felt sincere and not overbearing.

I wonder if, in fifty years, my two sons will be able to look back at this moment and be able to reference it as a turning point or some sort of milestone in the history of cinema.

Comments

No comments yet. Log in and be the first!

  BENCHMARKS  
Loading Time: Base Classes  0.0014
Controller Execution Time ( Members / Movie Detail )  0.0250
Total Execution Time  0.0264
  GET DATA  
No GET data exists
  MEMORY USAGE  
547,928 bytes
  POST DATA  
No POST data exists
  URI STRING  
members/sensoria/movie_detail/7305
  CLASS/METHOD  
members/movie_detail
  DATABASE:  movielogr_dev (Members:$db)   QUERIES: 17 (0.0055 seconds)  (Hide)
0.0004   SELECT 1
FROM `ml_sessions`
WHERE `id` = '69f0807bf0058dfc0da224447554ee406e35c857'
AND `ip_address` = '216.73.216.111' 
0.0002   SELECT GET_LOCK('2b036dadad10baee50c3b78271e1a767', 300) AS ci_session_lock 
0.0002   SELECT `data`
FROM `ml_sessions`
WHERE `id` = '69f0807bf0058dfc0da224447554ee406e35c857'
AND `ip_address` = '216.73.216.111' 
0.0003   SELECT `username`, `user_id`
FROM `ml_users`
WHERE `username` = 'sensoria'
 LIMIT 1 
0.0003   SELECT `MV`.`title_id`, `MT`.`tmdb_id`
FROM `ml_movie_titles` `MT`
LEFT JOIN `ml_movies` `MV` ON `MV`.`title_id` = `MT`.`title_id`
WHERE `MV`.`movie_id` = 7305
AND `MV`.`user_id` = 1
 LIMIT 1 
0.0003   SELECT `star_rating`
FROM `ml_users`
WHERE `ml_users`.`user_id` = 1
 LIMIT 1 
0.0002   SET SESSION group_concat_max_len = 12288 
0.0014   SELECT `MV`.`title_id`, `MV`.`movie_id`, COUNT(DISTINCT MV.title_id) AS mv_count, `title`, `prefix`, `year`, `imdb_link`, `MT`.`imdb_id`, `MT`.`tmdb_id`, `overview`, `certification`, `runtime`, `genre_id_01`, `genre_id_02`, `genre_id_03`, MAX(MP.filename) AS filename, `G1`.`genre_name` AS `genre_name_01`, `G2`.`genre_name` AS `genre_name_02`, `G3`.`genre_name` AS `genre_name_03`, `date_viewed`, `notes`, `MV`.`format_id`, `FMT`.`format_name`, `MV`.`source_id`, `SRC`.`source_name`, `MV`.`device_id`, `DVC`.`device_name`, `MV`.`rating_id`, `STR`.`star_rating`, `rewatch`, GROUP_CONCAT(DISTINCT(DR.director_name) ORDER BY DR.tmdb_director_id ASC SEPARATOR "|") AS directors, GROUP_CONCAT(DISTINCT(DR.tmdb_director_id) ORDER BY DR.tmdb_director_id ASC SEPARATOR "|") AS director_ids, GROUP_CONCAT(DISTINCT(ACT.actor_name) ORDER BY ACT.tmdb_actor_id ASC SEPARATOR "|") AS actors, GROUP_CONCAT(DISTINCT(ACT.tmdb_actor_id) ORDER BY ACT.tmdb_actor_id ASC SEPARATOR "|") AS actor_ids
FROM `ml_movie_titles` `MT`
LEFT JOIN `ml_movies` `MV` ON `MV`.`title_id` = `MT`.`title_id`
LEFT JOIN `ml_movie_posters` `MP` ON `MV`.`title_id` = `MP`.`title_id`
LEFT JOIN `ml_lookup_genres` `G1` ON `MV`.`genre_id_01` = `G1`.`genre_id`
LEFT JOIN `ml_lookup_genres` `G2` ON `MV`.`genre_id_02` = `G2`.`genre_id`
LEFT JOIN `ml_lookup_genres` `G3` ON `MV`.`genre_id_03` = `G3`.`genre_id`
LEFT JOIN `ml_lookup_formats` `FMT` ON `MV`.`format_id` = `FMT`.`format_id`
LEFT JOIN `ml_lookup_sources` `SRC` ON `MV`.`source_id` = `SRC`.`source_id`
LEFT JOIN `ml_lookup_devices` `DVC` ON `MV`.`device_id` = `DVC`.`device_id`
LEFT JOIN `ml_movie_ratings_ten_star` `STR` ON `MV`.`rating_id` = `STR`.`rating_id`
LEFT JOIN `ml_junction_movies_directors` `JMD` ON `MT`.`title_id` = `JMD`.`title_id`
LEFT JOIN `ml_directors_new` `DR` ON `JMD`.`tmdb_director_id` = `DR`.`tmdb_director_id`
LEFT JOIN `ml_junction_movies_actors` `JMA` ON `MT`.`title_id` = `JMA`.`title_id`
LEFT JOIN `ml_actors_new` `ACT` ON `JMA`.`tmdb_actor_id` = `ACT`.`tmdb_actor_id`
WHERE `MV`.`movie_id` = 7305
AND `MV`.`user_id` = 1
ORDER BY `date_viewed` DESC 
0.0004   SET SESSION group_concat_max_len = 1024 
0.0003   SELECT `event_title`, `JME`.`event_id`
FROM `ml_junction_movies_events` `JME`
LEFT JOIN `ml_movie_events` `EV` ON `JME`.`event_id` = `EV`.`event_id`
WHERE `JME`.`movie_id` = 7305 
0.0002   SELECT `tag`, `JMT`.`tag_id`
FROM `ml_junction_movies_tags` `JMT`
LEFT JOIN `ml_tags` `MT` ON `JMT`.`tag_id` = `MT`.`tag_id`
WHERE `JMT`.`movie_id` = 7305 
0.0002   SELECT `star_rating`
FROM `ml_users`
WHERE `ml_users`.`user_id` = 1
 LIMIT 1 
0.0002   SELECT `rating_id`
FROM `ml_movies` `MV`
WHERE `MV`.`user_id` = 1
AND `MV`.`movie_id` = 7305
 LIMIT 1 
0.0002   SELECT `star_rating`
FROM `ml_movie_ratings_ten_star` `MR`
WHERE `MR`.`rating_id` = '18'
 LIMIT 1 
0.0003   SELECT `MV2`.`date_viewed`, `MV2`.`movie_id`
FROM `ml_movies` `MV`
LEFT JOIN `ml_movies` `MV2` ON `MV`.`title_id` = `MV2`.`title_id` AND `MV`.`user_id` = `MV2`.`user_id`
WHERE `MV`.`user_id` = 1
AND `MV`.`movie_id` = 7305
GROUP BY `MV2`.`movie_id`
ORDER BY `MV2`.`date_viewed` DESC 
0.0002   SELECT `comment_id`, `comment`, `commenter_id`, `timestamp`, `username`, `email_address`
FROM `ml_comments` `MC`
JOIN `ml_users` `MU` ON `MU`.`user_id` = `MC`.`commenter_id`
WHERE `movie_id` = 7305 
0.0003   SELECT `username`, `date_viewed`, `MV`.`movie_id`
FROM `ml_users` `MU`
JOIN `ml_movies` `MV` ON `MV`.`user_id` = `MU`.`user_id`
JOIN `ml_movie_titles` `MT` ON `MT`.`title_id` = `MV`.`title_id`
WHERE `MT`.`title_id` = 4222
ORDER BY `date_viewed` DESC
 LIMIT 10 
  HTTP HEADERS  (Show)
  SESSION DATA  (Show)
  CONFIG VARIABLES  (Show)